A model for image retrieval tasks for creative multimedia

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A model for image retrieval tasks for creative multimedia

Creative multimedia

Roslina Othman Faculty of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur, Malaysia

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Abstract Purpose – This paper seeks to report on the study that proposed a model of image retrieval tasks for creative multimedia. The aim of this model was to understand the purpose of the tasks, intended use of the images, mode of query submission, nature of the keywords given by the users, and relevance criteria. Design/methodology/approach – A survey was done to compile a total of 35 image retrieval tasks from 35 academic staff members at Faculty of ICT, International Islamic University Malaysia, and Faculty of Creative Multimedia, Malaysia. A search using Google Image Search category was carried out to find images on the web that met the intended use of the academic staff members. Findings – Findings revealed that images were mostly intended for analysis, decorations, design, illustrations, image processing, and inspiration. Users preferred linguistic query mode, and visual query mode if they had a sample of the image. Most users requested images with captions for making the relevance judgment. Technical attributes, topicality, and completeness were the most important relevance criteria. Users’ keywords were of abstract and concrete elements, and were expressed in a visual way and as a subject. Images decided as relevant ranged from an object in the image to the whole image. This model reflected similar findings to other studies with some variations. Practical implications – Results are useful for understanding the nature of image retrieval tasks for the area of creative multimedia. Originality/value – This paper developed a model of image retrieval tasks in the area of creative multimedia, and offers a value in understanding the tasks that are intended to meet the demand of the Creative Multimedia Industry established in Malaysia. Keywords Information retrieval, Multimedia Paper type Research paper

Introduction In today’s world we witness the use of images – as illustrations in online articles and research reports, as decorations in presentation slides, as multimedia short messages (mms), and as a product image displayed on online advertisements. Images, be they in the form of photographs, icons, and animation, attract people to read or browse the content of the web pages and documents. In Malaysia, the Multimedia SuperCorridor planned to set up a Creative Multimedia Industry, defined as: . . . the industries using and broadcasting moving images, computer graphics, sound and text as fundamental components to facilitate communications, and for entertainment, planning, design, simulation, commerce and education; the Industry includes Film & TV, games, animation, heritage projects, digital community projects, music, fashion, live performance, product and engineering design as well as other arts and cultural related industries where creativity is the economic resource” (MSC Magazine, 2003).

Even before the establishment of this industry, there have already been quite a number of projects undertaken at many universities (FCM, 2003; FITC, 2003), which heavily

Performance Measurement and Metrics Vol. 6 No. 2, 2005 pp. 115-131 q Emerald Group Publishing Limited 1467-8047 DOI 10.1108/14678040510607821

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involved compilation of images for reference and review. Grants at the national level were made available, and multimedia has long been included as one of the priorities areas for research (MOSTE, 2002). The establishment of this new industry would create more image retrieval tasks and higher demand for images as reference. Thus there is a need to develop a model for an image retrieval task for creative multimedia. There are no studies conducted on image retrieval tasks in Malaysia, and for creative multimedia. Since 1999 there are now more than 180 million images available on the web with the number growing daily (Ozmutlu et al., 2003), and which can be searched through many web-based retrieval systems and search engines. Google (http://images.google. com/) is the most popularly used search engine (TASI, 2003), and claimed that it indexed more than 425 million images (Google, 2003). A preliminary study conducted by the author revealed that the academic staff members at the International Islamic University and Multimedia University in Malaysia searched for images on the web using Google to complete their image retrieval tasks (Othman, 2002). The aim of this study was to develop a model of image retrieval tasks in the area of creative multimedia due to its heavy manipulation of images. This model would help understand the uses of images, user’s query mode, user’s keywords, level of details for relevance judgment, and relevance criteria for images needed from the web. The model would provide clues for developing the content and features for an image retrieval system in the area of creative multimedia. Fidel (1997) and Rasmussen (1997) stressed that studies on users need for images are still lacking, before an image retrieval system could be effectively designed and evaluated. Previous studies Studies related to image retrieval tasks were done in the field of art history (Hastings, 1995; Chen, 2001), medicine (Bucci et al., 1996), history (Choi and Rasmussen, 2002), and crime investigation (Pastra et al., 2003). Even though image retrieval tasks vary from one area to another since users have information needs specific to their areas and domain applications (Dervin and Nilan, 1986), some findings might have possible applications for creative multimedia. Image retrieval tasks were studied in relation to: . image use (Conniss et al., 2000); . image query mode (Enser, 1993; Chen, 2001); . queries and search terms given to complete the image retrieval tasks (Keister, 1994; Goodrum and Spink, 2001; and Jorgensen, 1998); and . users’ relevance criteria before and after the conduct of searches (Choi and Rasmussen). Conniss et al. (2000) identified seven classes of image use: (1) Illustration. Use of images to represent what is being referred to in the text. (2) Information processing. Using the data contained in the image. (3) Information dissemination. Using the information contained in the image and passed on to others. (4) Learning. Use of image content to gain knowledge.

(5) Generation of ideas. Use of images as inspiration. (6) Aesthetic value. Use of images for decorative purposes. (7) Emotive or persuasive. Use of images to stimulate emotions or a particular idea. Their studies indicated that the intended use of an image affected the way users search for images. Enser (1993) developed four modes of image retrieval: (1) Linguistic query mode-linguistic search mode. (2) Visual query mode-visual search mode. (3) Visual query mode-linguistic search mode. (4) Linguistic query mode-visual search mode. Chen (2001) noted that visual query mode-visual search mode was mostly reported in specialized subject areas. This study would explore on the possibility that users might be providing linguistic query mode, or visual query mode, or both, and the situation that prompted such query mode. In addition to the different query mode, the study would ask the users if they would like to include a feature allowing a visual search mode in an image retrieval system. Keister (1994) found that most of the queries for images submitted to the National Library of Medicine consisted of abstract and concrete image elements. She found that queries were formulated by the intended use. Her study revealed that users submitted their queries in words and in three ways: visual description, subject, and the exact caption or title of the image. Her findings could be a reference point for user’s description of the images needed in this study. Goodrum and Spink (2001) identified in their study which involved 33,149 queries in Excite that users’ terms could be classified into image terms, modifiers, sexual, cost, gender, people, and others like download and index. Jorgensen (1998) found in her study that users’ terms could be classified into seven attributes: object, people, social status, color, body part, location-specific, and activity. This study could have similar or different classification of the terms given by the users to describe the images they need. Choi and Rasmussen (2002) identified nine relevance criteria: (1) topicality; (2) accuracy; (3) time frame; (4) suggestiveness; (5) novelty; (6) completeness; (7) accessibility; (8) appeal of information; and (9) technical attributes of images. Topicality includes criteria related to tasks, accuracy for accurately representing the images needed, time frame for period of the image, suggestiveness for images that generate new ideas, and novelty for images that are new to users. Completeness is for

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images containing all the required details, accessibility for image availability, appeal of information for images that are interesting to users, and technical attributes for color etc. They found that topicality was the most important criteria for pre- and post-search, followed by accuracy and completeness before the search, which then changed to time frame and accessibility after the search. Choi and Rasmussen (2002) also added eight non-visual attributes as relevance criteria: title, date of publication, name of the photographer or creator, subject descriptors, notes, and medium, collection information, and repository information. To conclude, this study would use similar attributes to classify the relevance criteria given by the users before and after browsing the images retrieved from the web, and would see if these users shared similar ranking of attributes. Proposed model for image retrieval task The proposed model of image retrieval task for creative multimedia in an academic environment consisted of: . purpose of retrieving images; . image use; . modes of query expression and search; . users’ description of the images; and . relevance criteria. The results gathered for this study will be discussed against the results from previous studies. Methodology A total of 35 image retrieval tasks were gathered from 35 academic staff members[1] at Faculty of Information and Communication Technology, International Islamic University Malaysia and at Faculty of Creative Multimedia, Multimedia University, Malaysia. The compilation of image retrieval tasks was done at two stages through telephone interviews: (1) compilation of image retrieval tasks; and (2) relevance judgment for images retrieved from the web. Searches were carried out by the researcher in Google’s Image Search category from July to December 2003. Detailed responses are presented in the Appendix. Findings and discussion The findings are discussed in the following sequence: image retrieval tasks and its comparison with previous studies. Image retrieval tasks Purpose of task. The 35 image retrieval tasks shown in the Appendix could be categorized into six classes of purpose (Table I). The purpose was actually related to the user’s responsibilities at the university, and such responsibilities are counted for promotion.

Images were much needed for research and publication, and for both purposes, research grants were given. The provision of research grants encouraged the needs and acquisition of images, even through purchase. Based on the purpose of the task and the support attached to it, the searcher would know to what extent the user would go to complete the tasks. Out of these 35 tasks, 14 attempted to fulfill two purposes: research and publication (eight); research and IT projects (three); teaching and IT projects (two); and supervision and publication (one). The IT projects were mostly part of the curriculum requirements and were aimed for student’s award related to creative multimedia. As for teaching, the academic staff members mentioned that their students expected slides with images and creativity from their lecturers. Thus for all purposes, relevant images were required or needed to ensure the quality of the work. Other factors that influenced research and publication as having the highest count included the faculty member’s attitude of creating their “niche” at the faculty while maintaining the originality and research values of the project, which later to be extended to publication and acceptance in the market and the Industry. Some academic staff members expressed their feeling that specific images would be hard to find on the web and from other sources, and thus the tasks required them to develop their own collections. The availability of research grants would very much assisted them on this matter. Intended use of images: the intended uses of images needed fall into six categories (Table II): (1) analysis; (2) decorations; (3) design; (4) illustrations; (5) image processing; and (6) inspiration.

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There were images serving more than one uses for the same task. The images needed for the “Life of a Bedouin” were intended for analysis of the lifestyle and culture, for design of animation, and illustrations in a book on animation. In the case of design category, images needed for the task interior design would be used as texture in one plan type and also as an object in another type. The best example was the image of a ceiling, which provided texture for a drawing of a ceiling and used as a ceiling itself in another design option. In the case of the Malay manuscripts, an image of a manuscript was used for analysis of originality and also as an illustration of a manuscript written by a Malay scholar and annotated by his students. Purpose Research IT project Publication Teaching Consultancy project Supervision

Number of tasks 14 11 10 10 2 2

Table I. Purpose of image retrieval tasks

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Image use Analysis

120 Decorations

Design

Illustrations or visualization

Image processing and pattern/color recognition

Inspiration

Table II. Image retrieval tasks are divided into six categories of image use

Image retrieval tasks Research 1. 100 best photos 2. Close-up of nature 3. Library buildings 4. Signage in PJ Research and IT projects 1. Art form 2. Award-winning rural landscape IT project 1. Storytelling contest 2. Web edutainment – framework 3. Web page design Object IT project 1. Geometrical images 2. Images related to Islam Teaching and IT project 1. Company logo Consultancy 1. Interior design Research and publication 1. Life of a Bedouin Teaching 1. Animal abuse 2. Company logo 3. Ergonometric computer workstations and fixtures 4. Graphical presentation 5. Images of war 6. Movie clips 7. Movie camera 8. Network components 9. Operating system 10. Pollution Research and publication 1. Arabic alphabets in letters 2. Transportation in nineteenth century Publication 1. Calligraphy 2. License plate Research and publication 1. Life of a Bedouin 2. Malay design Research and IT project 1. Art form 2. Award-winning rural landscape

Research and publication 1. Life of a Bedouin 2. Malay design 3. Malay manuscripts 4. Port of Malacca – fifteenth century

Publication 1. Conference paper

Texture Consultancy 1. Interior design 2. Real-time visualization and animation

Publication 1. Arabic alphabets in letters 2. Calligraphy 3. License plate 4. Life of a Bedouin 5. Malay design 6. Malay manuscripts 7. Port of Malacca – fifteenth century 8. X-ray images Research 1. Signage in PJ IT project 1. Maps Supervision Robots for re-cycling Supervision and research 1. X-ray images Teaching and IT project 1. Company logo 2. Movie clips Research 1. 100 best photos IT project 1. Web edutainment – framework

Images used as illustrations in teaching scored the highest and again possibly due to the expectation of the teaching quality at the two faculties. The analysis category involved using images as the subject of study and did not involve image manipulation. The 100 best photos, for example, was intended to study the nature of photos awarded as best photos by the National Geographic Society; while the Signage in PJ was to analyze the changes in a town, Petaling Jaya, caused by the new constructions; and the Port of Malacca – fifteenth century was to trace the real situation of Malacca during its golden civilization. The decorations, design, and illustrations or visualization categories involved images requiring minimal manipulation, like “copy and paste”, trimming, and resizing. Design category also included texture of the images and involved texture mapping and rendering. The image processing and pattern/color recognition category involved images as the content of a prototype, which required a high degree of image manipulation, like image de-blurring and enhancement. The inspiration category consisted of images used to generate ideas and not for use in a project. Mode of query expression (Table III). Queries were submitted in linguistic mode when there was no example of the images and when the academic staff members normally expressed them in such mode. No submission was done in a visual mode alone. All of the academic staff members felt that text is still needed to express their queries. Combined linguistic and visual mode consisted of tasks that were mostly related to image processing and design. Some of the samples of images were given since they were available from previous searches and were submitted as a clarification to the search requirements. All academic staff members who participated in this study mentioned that a visual search mode would be relevant if they had a sample of an image and would like to find similar images to select the best ones. For these image retrieval tasks, they were looking for different images. Level of detail (Table III). Some users decided that image alone was sufficient for relevance judgments because the images must be technically qualified for processing Description Mode of query expression Linguistic Visualization Linguistic and visualization Level of details Image Image with caption Image with detailed information User’s relevance criteria Technical attributes of images Topicality Completeness Time frame Accuracy Appeal of information Suggestiveness Accessibility

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Number of tasks 22 0 13 8 18 9 21 16 14 3 1 1 1 0

Table III. Mode of query expression, level of details for relevance judgment, and relevance criteria identified in this study

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and required no authentication. Image with caption was required to ensure accuracy in interpretation; for example the X-ray images with a caption on the body part. In this study, this level of details scored the highest count, which indicated that majority of the academic staff members were cautious in deciding the relevance of the images. Detailed information was needed for analysis, authentication, and as information not depicted in the image itself. Out of nine users requesting for detailed information, seven users intended to use the images for analysis. Relevance criteria (Table III). Most images in this study involved analysis and image manipulation, and thus majority of the tasks gave technical attributes as the relevance criteria. Technical attributes criterion included resolution, size, color, and dimension. Topicality and completeness ranked second and third which indicated that images must be right on the topic and have all the objects specified. Time frame was an important criterion for Port of Malacca – fifteenth century, which happened to be an important element in the research itself. User’s keywords (Appendix): Most of the keywords given by the users described the images needed, and there were 21 tasks in which the keywords need refinement. Additional terms were developed from the user’s search requirements to retrieve more of images that were possibly relevant to the tasks. Both user’s and additional keywords were of abstract and concrete elements of the images. Users described the images needed in a visual way, like Arabic alphabets, and as a subject, e.g. Malay design. The sample of images provided clarification on what was needed, i.e. objects in the image. Keywords allowing a lateral approach and additional steps, like browsing the web site of the relevant images, were compiled for all tasks. For example, the user, who was aiming for completeness, provided the components of a movie camera as the keywords, and the brand name of the camera as the additional keywords. Analysis of relevant images Table IV shows the number of images judged as relevant. Out of the 35 tasks, 33 tasks found relevant images, which indicated that there were images available on the web that met the intended use of the users. There were two tasks that retrieved some images and none were relevant to the user: signage in PJ and Port of Malacca in the fifteenth century. In both cases, the tasks were very specialized in nature and original in idea. It was suspected that such images were not available on the web. A discussion between the user and several historians revealed that there was a possibility that there were no images on Port of Malacca in the fifteenth century even in a specialized database. The web sites from which the relevant images were retrieved could be categorized into computer games, image gallery, associations, individuals, organizations, companies, and news. The task real-time visualization and animation has the highest number of relevant images, and all these images were retrieved from web sites offering computer games with most of them could be easily downloaded. Images on pollution came from image gallery like Photoshop, and images on 100 best photos came from the image gallery of National Geographic Society. Images on animal abuse came from associations and individuals who were against such cruelty. The tasks for Malay manuscripts and Malay design retrieved relevant images from the web site for an organization, i.e.

No.

Image retrieval task

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35.

100 best photos Animal abuse Arabic alphabets in letter Art form Award-winning rural landscape Calligraphy Close-up of nature Company logo Conference paper – research on images Ergonometric computer workstations and fixtures Geometrical images Graphical presentation Images of war Images related to Islam Interior design Library buildings License plate Life of a Bedouin Malay design Malay manuscripts Maps Movie camera Movie clips Network components Operating system Pollution Port of Malacca – fifteenth century Real-time visualization and animation Robots for re-cycling Signage in PJ Storytelling contest – Classical stories for children Transportation – nineteenth century Web edutainment – framework Web page design – icons X-ray images

Number of relevant images retrieved 13 33 3 28 1 35 31 15 10 17 5 4 25 26 9 4 2 1 6 4 25 37 13 3 1 43 0 76 11 0 21 5 10 28 3

Archive Division. The images for ergonomic computer workstations and fixtures were retrieved from company’s web site, and images of war were from the news web site. The images that were judged as relevant and met their intended use ranged from one object in the image retrieved to the whole image itself. Some of the images had to be merged as one new image since the object required was available as separate parts in many images. Relevant images for the “Art form” were further used to find articles discussing the topic of “Art form” and similar images sufficient to build its own category. The faculty member who requested the images for “Malay manuscript” was amazed to know that there were relevant images on the topic available on the web, and felt that he would continue with his task since his compilation would cover the artifacts in the museum and archive division. These images retrieved from the web would be good addition to his literature review section.

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Table IV. Analysis of the relevant images

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Analysis of the model The results from this study were quite similar to the findings from previous studies. The categories of image use identified in this study were more specific to producing a multimedia design. The categories of intended use of images were similar to Conniss et al. (2000), however, none of the users fell into the categories of information dissemination and emotive or persuasive. The visual query mode depended very much on the availability of a sample, and thus the users did not expect a visual search mode as an important feature in an image retrieval system. The keywords given by the users were of similar category as the one given by Keister, i.e. abstract and concrete elements of the images, and some of those derived from Jorgensen’s seven attributes, which were object, people, and location. Some keywords were expressed in a visual way and as a subject with none as the exact title of the images. None of the studies explored the level of details needed for relevance judgments. This study revealed that some users required a detailed description of the image before deciding whether the images met their intended use. Almost all the users who requested for detailed information intended to use the images for analysis. Even though relevance criteria were similar to the ones developed by Choi and Rasmussen (2002), technical attributes was the most important criteria in this study with completeness and topicality as second. Topicality was the most important criteria in the study conducted by Choi and Rasmussen (2002), and was still among the most important one in this study. None of the academic staff members expressed their concern for the non-visual attributes given by Choi and Rasmussen (2002). Conclusion The area of creative multimedia covers a wide range of subjects: art, computer designs and graphics, history, culture and heritage, broadcasting, and engineering. In most cases, images needed must meet a certain standard of technical attributes for further processing, analysis, and manipulation. A model for an image retrieval task in this particular area is needed especially when the demand for images increased due to the establishment of creative multimedia industry and the demand for archiving the completed projects for future reference, which also consisted of images. The model resulted from this study had similar findings as those from previous studies since the area of creative multimedia covers similar images like those for art, art history, and medicine. The differences were only in terms of relevance criteria judged as the most important and having the feature allowing a visual search mode for an image retrieval system. This study revealed that there were images on the web that satisfied the intended use described by the users; and the range of relevance varied from an object in the image to the whole image itself. The model of an image retrieval task for creative multimedia developed from this study revealed that the content for an image retrieval system must give serious consideration to technical attributes and features allowing linguistic and visual query modes. The system must also consider the level of details or information that should be attached to the images in its database. Note 1. The terms academic staff members and users are used interchangeably in this paper.

References Bucci, G., Cagnoni, S. and De Dominicis, R. (1996), “Integrating content-based retrieval in a medical image reference database”, Computerized Medical Imaging and Graphics, Vol. 20, pp. 231-41. Chen, H. (2001), “An analysis of image retrieval tasks in the field of art history”, Information Processing and Management, Vol. 37, pp. 701-20. Choi, Y. and Rasmussen, E.M. (2002), “Users’ relevance criteria in image retrieval in American history”, Information Processing and Management, Vol. 38, pp. 695-726. Conniss, L.R., Ashford, A.J. and Graham, M.E. (2000), Information-Seeking Behaviour in Image Retrieval: VISOR I Final Report (Library and Information Commission Research Report: 95), Institute for Image Data Research, Newcastle. Dervin, B. and Nilan, M. (1986), “Information needs and uses”, Annual Review of Information Science and Technology, Vol. 21, pp. 3-33. Enser, P.G.B. (1993), “Query analysis in a visual information retrieval context”, Journal of Documents and Text Management, Vol. 1, pp. 25-52. Faculty of Creative Multimedia (FCM) (2003), Multimedia University, Selangor Darul Ehsan, available at: www.mmu.edu.my/fcm (accessed May 2003). Faculty of Information and Technology Communication (FITC) (2003), “Kulliyyah of Information and Communication Technology”, available at: http://kict.iiu.edu.my/ (accessed June 2003). Fidel, R. (1997), “The image retrieval task: implications for the design and evaluation of image databases”, The New Review of Hypermedia and Multimedia, Vol. 3, pp. 181-99. Goodrum, A. and Spink, A. (2001), “Image searching on the Excite web search engine”, Information Processing and Management, Vol. 37, pp. 295-311. Google (2003), web page, available at: http://images.google.com Hastings, S.K. (1995), “Query categories in a study of intellectual access to digitized art images”, Proceedings of the 58th Annual Meeting of the American Society for Information Science, Chicago, IL, Vol. 32, pp. 3-8. Jorgensen, C. (1998), “Attributes of image-describing tasks”, Information Processing and Management, Vol. 34 Nos 2/3, pp. 161-74. Keister, L. (1994), “User types and queries: impact on image access systems”, in Fidel, R. (Ed.), Challenges in Indexing Electronic Text and Images, Learned Information, Medford, NJ, pp. 7-22. Ministry of Science, Technology, and the Environment (MOSTE) (2002), User’s Manual for IRPA Programme, 8th Malaysian Plan, MOSTE, Kuala Lumpur. MSC Magazine (2003), “Multimedia SuperCorridor (MSC)”, MSC Magazine, available at: http:// mscdotcomm.mdc.com.my/msc.comm/MSC%20Magazine_enter%20the%20creatives.htm (accessed June 2003). Othman, R. (2002), “Estimating recall values for an image retrieval system for creative multimedia”, Research Report, IIUM Research Center, Gombak, unpublished. Ozmutlu, S., Spink, A. and Ozmutlu, H.C. (2003), “Multimedia web-searching trends: 1997-2001”, Information Processing and Management, Vol. 39, pp. 611-21. Pastra, K., Saggion, H. and Wilks, Y. (2003), “Extracting relational facts for indexing and retrieval of crime-scene photographs”, Knowledge-Based Systems, Vol. 16 Nos 5/6, pp. 313-20. Rasmussen, E.M. (1997), “Indexing images”, Annual Review of Information Science and Technology, Vol. 32, pp. 169-96. TASI (2003), “A review of search engines”, TASI Resources, available at: www.tasi.ac.uk/ resources/searchengines.html (accessed 11 July).

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Table AI. Details of the image retrieval tasks

100 best photos

Animal abuse

Arabic alphabets in letter

Art form

Award-winning rural landscape

Calligraphy

1.

2.

3.

4.

5.

6.

Task

Domestic animals on farm

Best photos ever published by National Geographic Society

Search requirements

Painting, sculpture, and photographs

Linguistic

Linguistic Visualization

Linguistic

Linguistic

Mode of query

Research and IT project

Linguistic Photograph of rural landscape that won either a local or an international award Research and publication Calligraphy form Linguistic Visualization

Research and IT project

Research and publication Handwritten letters

Teaching

Research and IT project

Purpose

User’s keyword: Calligraphy Additional keywords: Arabic calligraphy, Islamic calligraphy

User’s keyword: Animal abuse Additional keywords: Animal cruelty, pet abuse, injured cat, cockfighting User’s keyworda: Arabic alphabets Additional keywords: Arabic letters, Arabic writings, Arabic document User’s keyword: Art form Additional keywords: Conceptual art, earth art, body art, man-made art User’s keyword: Rural landscape

User’s keyword: 100 best photo

Keywords/search terms

Technical quality Completeness – thickness, dots, slope, sharp edges

Topicality – awardwinning Technical quality

Topicality – man-made art and preferably images embedded in article on art

Technical quality

Topicality – 100 best photos (National Geographic Society) Technical quality Completeness – display action of abuse or effect of the abuse (evidence)

Relevance criteria

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Image with detailed information on title and theme of competition, and winning criteria Image

Image with detailed information on creator and meaning of the art

Image

Image with caption

Image with caption

Information required for making relevance judgments

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12.

11.

10.

9.

8.

7.

Teaching

IT project

Ergonometric computer workstations and fixtures Geometrical images

Teaching

Geometrical images 2D/3D

Publication

Conference paper – research on images

Graphical presentation

Ergonometric products for existing part of a computer workstation

Teaching and IT project

Company logo

Data structure Layout of database design

Bone X-rays Calligraphy Edutainment web site

Logo of company associated with hardware

Plants Flowers Nature design for products like seat cover

Research

Close-up of nature

Search requirements

Purpose

Task

Linguistic

Linguistic Visualization

Linguistic

Linguistic Visualization

Linguistic

Linguistic Visualization

Mode of query

User’s keyword: Geometrical image Additional keywords: Geometrical shape User’s keywords: Data structure, database design

User’s keywords: Plants, flowers Additional keywords: Close-up plant, close-up flowers User’s keywords: Company logo, SUN, IBM Additional keywords: SUN logo, IBM logo, DELL logo, Acer logo, Fujitsu logo User’s keywords: X-rays, calligraphy, edutainment Additional keywords: Bone X-ray, Arabic calligraphy, Islamic edutainment, Islamic software User’s keyword: Ergonomic

Keywords/search terms

Completeness – body parts, human-product interaction, sitting position Completeness Topicality – computer-generated images (after the search) Technical quality

Technical quality

Technical quality

Topicality – close-up and functional texture Technical quality

Relevance criteria

(continued)

Image with caption

Image with caption

Image with caption

Image and caption

Image

Image

Information required for making relevance judgments

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Table AI.

Images of war

Images related to Islam

Interior design

Library buildings

License plate

Life of a Bedouin

14.

15.

16.

17.

18.

Table AI.

13.

Task

Mode of query

Linguistic

Linguistic Visualization

Linguistic Visualization Research and publication Bedouin, face, tent desert Linguistic life, clothing, belongings, community

Traditional buildings Modern buildings

Texture and object for interior design

Mosque, al-Quran, verses Linguistic from al-Quran and al-Hadith

Images of war consisting Linguistic of people with emotion

Search requirements

Research and publication License plate

Research

Consultancy project

IT project

Teaching

Purpose

User’s keyword: License plate User’s keyword: Bedouin

User’s keywords: Mosque, al-Quran, Hadith Additional keywords: al-Quran verses, prophet’s sayings User’s keyword: Interior design Additional keywords: Kitchen, hall, dining room, family room, bedroom, bathroom, toilet, sofa, coffee table, ceiling fan, dining table, window curtain User’s keyword: Library building

User’s keyword: War Additional keyword: Iraq war

Keywords/search terms

Technical quality Completeness Technical quality Completeness

Completeness – architectural design

Topicality – interior design for main hall and library, types of materials Technical quality

(continued)

Image with detailed information of their life

Image with detailed information on title, name of the institution and designers, and design Image

Image with caption

Completeness – emotion Image with caption Topicality – photos must appear in news, events, and must have people Time frame – recent war Topicality – animation, Image colorful Technical quality

Relevance criteria

128 Information required for making relevance judgments

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23.

22.

21.

20.

19.

Research and publication Digitized manuscripts

IT project

Teaching

Teaching and IT project

Malay manuscripts

Maps

Movie camera

Movie clips

Linguistic

Linguistic Visualization

Linguistic Visualization

Mode of query

Samples of angles/shots of movie clips

Linguistic

Components of the movie Linguistic camera

Geographical information system

Research and publication Malay design in traditional Malay products

Malay design

Search requirements

Purpose

Task User’s keyword: Malay design Additional keywords: Kukur kelapa, keris, rumah melayu, Malay tombstone, congkak User’s keyword: Malay manuscripts Additional keywords: Manuskrip melayu User’s keyword: Map Additional keywords: Map Malaysia, map and name of state and town User’s keywords: Movement, shutter, viewfinder, lenses, drive, magazines, features, accessories Additional keywords: Arriflex, Beaulieu, Mitchel, Eclair User’s keywords: Movie poster/clips Additional keyword: Movie and title of the movie

Keywords/search terms

Image

(continued)

Image with caption Topicality – demonstrate the composition of any scene, medium shots – waist-up, camera angle 45 degrees

Completeness – movement, shutter, viewfinder, lenses, drive, magazine, features, accessories

Image with details on date and authors

Completeness – contain narration and commentary Topicality – originality Topicality – still image Technical quality

Image with caption

Image with detailed information on products

Completeness – detailed view Technical quality

Relevance criteria

Information required for making relevance judgments

Creative multimedia

129

Table AI.

Operating system

Pollution

Port of Malacca – fifteenth century

Real-time visualization and animation Robots for re-cycling

25.

26.

27.

28.

29.

Network components

Table AI.

24.

Task

Air Water Buildings Housing areas Construction areas Factories

Structure Layout

Network components

Search requirements

Supervision

Consultancy project

Bottle Color

Textured background

Research and publication Visualization of ports in Malacca in fifteenth century

Teaching

Teaching

Teaching

Purpose

Linguistic

Linguistic Visualization

Linguistic

Linguistic

Linguistic

Linguistic

Mode of query

User’s keywords: Texture background, terrain mapping User’s keyword: Recycling bottle Additional keywords: Color bottles, Pepsi bottles, Coca-Cola bottles, Sprite bottles, Seven Up bottles, F&N bottles

User’s keyword: Pollution Additional keywords: Air pollution, ocean pollution, water pollution, river pollution, smoke factories User’s keyword: Port of Malacca – fifteenth century

User’s keyword: Operating system

User’s keyword: Network components

Keywords/search terms

Time frame – artist must be alive and was in Malacca during the period Topicality – texture of real objects Technical quality Topicality – plastic bottle, solid/single color Technical quality

Completeness Time frame – latest products Topicality – Linux, Unix, Windows, and Solaris Completeness Completeness – Ocean pollution images must show the effects, e.g. dead fish Technical quality

Relevance criteria

130 (continued)

Image with caption

Image with caption

Image with detailed information of the artist and events

Image with caption

Image with detailed information on type of network and components Image with detailed information on the operating systems

Information required for making relevance judgments

PMM 6,2

35.

34.

33.

32.

31.

30.

IT project

Research and publication 8/16 grey scale

IT project

IT project

Supervision and publication

Storytelling contest – Classical stories for children

Transportation – nineteenth century

Web edutainment – framework

Web page design – icons

X-ray images

Cancer patients X-rays

Iconic navigator images

Icon Characters Background

Road sign Shop sign Malaysian bank notes

Research

Signage in PJ

Search requirements

Purpose

Task

Linguistic Visualization

Linguistic

Linguistic

Linguistic Visualization

Linguistic Visualization

Linguistic

Mode of query

User’s keyword: Transportation nineteenth century User’s keyword: Icon Additional keywords: Disney characters, Warner Bros characters, User’s keyword: Icon Additional keyword: Animated pointer User’s keyword: X-ray image Additional keyword: Cancer X-ray

User’s keyword: Petaling Jaya User’s keyword: Malaysian money Additional keywords: Ringgit, Malaysia

Keywords/search terms

Image with caption

Image with caption

Topicality – image must Image with caption be conversion of X-rays to digitized images Technical quality

Accuracy – pointer types Image

Appeal of information – attractive to toddlers Suggestiveness

Image Completeness – similar size Topicality – no “sample” watermark and must look exactly like the bank notes Technical quality Technical quality Image with caption

Technical quality

Relevance criteria

Information required for making relevance judgments

Creative multimedia

131

Table AI.