Knowledge Browsing with Superlinks

Knowledge Browsing with Superlinks Kavi Mahesh1 and Pallavi Karanth2 1

Department of Computer Science and Engineering PES Institute of Technology Ring Road, Banashankari 3rd Stage Bangalore-560085, India. [email protected]

2

Department of Computer Science and Engineering PES Institute of Technology Ring Road, Banashankari 3rd Stage Bangalore-560085, India. [email protected]

Abstract In this paper, we consider the requirements for effective browsing of conceptual knowledge of a domain. We outline two problems that do not have good solutions in present technology: complex semantic linking to represent conceptual relations from a domain, and semantic linking of conceptual elements to pieces of texts. We present a solution to these two problems and call it a Superlink that not only provides a richly structured representation of links but also suggests a typology of link semantics for connecting conceptual elements to relevant parts of texts. We provide an illustration of the implementation of Superlinks to enable effective browsing and navigation of conceptual knowledge along with associated multilingual texts in an example domain of Indian herbs and spices. Keywords : Knowledge Browser, Superlink, Knowledge Knowledge Organization, Ontology, Semantic Tagging.

Modeling,

1. INTRODUCTION An obvious benefit of computerization has been the digitization of texts along with their publication as hypertext on the World Wide Web and the ability to find relevant texts using search engines. However, from the point of view of managing human knowledge, this is not fully effective since most of the knowledge is still buried in unstructured texts. It is critical that at least knowledge of the conceptual core of each field of study is made explicit by representing it in well-structured hierarchies or networks, often called ontologies. Knowledge management requires effective technology for structuring both concept ontologies and the associated texts.

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Technology for creating and managing ontologies and other simpler classification systems (such as taxonomies and thesauri) is well developed. However, merely constructing an ontology that is disconnected from its source texts is not effective: it is difficult to verify the accuracy of the conceptual map represented in the ontology, to find further explanations and illustrations of concepts beyond the limited descriptions in the ontology, or to compare and analyze the conceptual maps of different source texts. Such linking is extremely important to provide legitimacy to the entries in the ontology, apart from facilitating the development of the ontology itself and enabling semantic interpretation of the texts so linked. This problem is further complicated by the introduction of texts in multiple languages some of which may be translations of one another. Thus, knowledge management requires not only digital representation of documents and other texts but also a representation of the structure of the text, a well-structured ontology of the concepts and relations in the texts and mappings to and from pieces of the text to elements of the ontology. The work presented in this paper outlines the design of a linking mechanism between elements of an ontology and the texts to which they relate. The design of such links, called Superlinks, has been implemented using the family of XML languages in a sample domain, namely, modeling and management of traditional knowledge of Indian herbs and spices. An extension to a web browser has been built through which users can explore an ontology together with associated texts moving from one to another seamlessly in semantically precise ways.

2. REQUIREMENTS FOR KNOWLEDGE BROWSING Knowledge browsing is not the same as web browsing. It involves browsing through structured conceptual knowledge, through hyperlinked texts, and navigating from one to the other in semantically meaningful ways where the user is never lost. We identify here two major problems in meeting the requirements of knowledge browsing using present web browsing technology using standard hypertext links.

2.1. Problem 1: Inadequacy of Hypertext Links Search, browsing and navigation1 complement each other in enabling retrieval and exploration of knowledge. While search has become ubiquitously available, browsing has been limited to clicking on hypertext links to jump from one page to another. Navigation has found a few other 1

The difference between navigation and browsing is that navigation has a known destination while browsing is exploratory and may not have a specific destination.

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popular mechanisms such as the familiar “explorer view” or tree-based hierarchical views and the not-so-familiar relational navigation [1]. A variety of fancier metaphors and visualizations have been tried [2] although none has withstood the tests of time and the likes and dislikes of users. Why do we need a mechanism more complex than the simple hypertext link to enable effective browsing and navigation of knowledge? Knowledge has a complex structure to it which is best seen as a graph or network of wellstructured concepts and relations. A critical aspect of the structure of knowledge is the semantics attached to the relations or links. Though this idea originated in the development of Semantic Networks [3] in Artificial Intelligence, it is missing from both hypertext links and tree-based visualization and navigation metaphors. Knowledge organization formalisms such as thesauri, taxonomies and the like [4], including those from linguistics (e.g., WordNet[5]) have addressed this problem by severely limiting the types and semantics of links that can be present. Another issue with hypertext links is the unit size of text to which a link can point. This is usually an entire document or web page or at best an approximate position in the text (i.e., an anchor tag whose name is #appended to the target URL of the link). This is inadequate since meaning often lies in smaller units of text such as sections, paragraphs, sentences, or even individual words and phrases. Although XPATH and XPOINTER languages have been designed specifically to enable more precise target references, current browsers do not support them.

2.2. Problem 2: Linking Conceptual Structures with Texts Ontologies or other classification systems such as taxonomies are essential for effective knowledge organization. However, the textual basis for the terms, concepts, relations and attributes in an ontology are typically not included in them, thereby raising questions of the “says who?” kind in the minds of the user. This often leads to lack of trust in the ontology or confusion, inconsistency, and so on. The pieces of texts from which the definition of a concept, for example, is obtained is not explicitly linked to the concept in the ontology. The obvious solution of including a hyperlink to a web page such as a Wikipedia page is not adequate to satisfy users’ needs. Users may want to know one or more texts that define the concept or relation, describe it, give an example for it, show a use of it, provide translations for it in different languages, or otherwise add to the information in the ontology in encyclopedic ways.

3. RELATED WORK Early work on interpreting text at the semantic level focused on natural language understanding at a deep semantic level [6]. Projects such as

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Mikrokosmos [7, 8] demonstrated this on a small scale. On the same lines, work in artificial intelligence on representing conceptual knowledge also took a deep semantic approach primarily using predicate logic as in the Cyc project for instance. Once again, knowledge bases such as Cyc could not be scaled up [9]. OpenCyc, an open source version of the commercial Cyc product, which followed a deep semantic approach, is like an unabridged dictionary for the machines. However, use of OpenCyc with open world web content has weaknesses [31] such as the upper ontology not being clean and current triple data model underlying RDF is absent in conventions of OpenCyc. In a more recent research thrust, the focus has been on sha llow semantics where both the sizes of ontologies and knowledge bases and the amount of text that can be mapped to the concepts have been scaled up significantly. Much of this work falls under the broad label of Semantic Web [10], although we are far from realizing a truly semantic web. In shallow semantics, formalisms for representing semantic and ontological information such as RDF, Resource Description Framework [11], RDFS, RDF Schema [12] and OWL, Web Ontology Language [13] have been standardized by the World-Wide Web Consortium (http://www.w3c.org). However, these are yet to become real standards. For instance, the revised standard, OWL 2, which has been proposed recently [14], differs from the original OWL in significant ways. Technology for creating and editing ontologies is well developed. The ontology editor called Protege developed by Stanford University [15] is quite popular. Commercial products such as Semantic Works by Altova.com are also available. These tools also support encoding of semantic tags using RDF. RDF storage and retrieval has also been scale d up in tools such as Sesame [16]. Many other tools such as KAON, Ontopia, OntoStudio and TopBraid are also quite popular as ontology editors. Work on linguistic semantics has also focused on the development of knowledge resources for representing the semantics of language and the meanings of wor ds in computational lexicons [17]. However, in this work, as in WordNet [5] for example, knowledge from texts is manually (or semiautomatically) extracted and encoded in the lexicon after which the texts themselves are discarded. Work on linking texts to ontologies has taken the approach of ontology-based annotation [18] wherein the researcher assumes that there is already an ontology for the domain of discourse of the text being analyzed. The problem is merely one of annotating pieces of the text mostly against concepts in the ontology (not relations among concepts). Apart from not supporting the concurrent development of the ontology itself from the texts, a crucial

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limitation of ontology-based annotation is that it only deals with texts that merely instantiate the conceptual knowledge in the ontology, as opposed to defining, explaining, illustrating or elaborating on the knowledge. It is as though the authoritative knowledge is present only in the ontology and the text is merely linearizing a part of that knowledge by rendering it in a natural language text. It is in this respect that the present work differs from ontologybased annotation: here, and in many real-world situations, source texts contain authoritative and definitional knowledge and, in annotating the text, it must be possible to extract that knowledge efficiently and encode it precisely to further develop the ontology. Work on ontology-based annotation has produced many tools such as BOEMIE [19], OntoGloss [20], Annotea [21] and OnTeA [22], which support both manual and semi-automatic annotation of texts in a chosen domain for which an ontology is available. They treat ontologies as pre-existing knowledge resources and do not contribute to the growth or development of the ontologies themselves. In a separate but significant development, the Wikipedia (http://www.wikipedia.org) has very successfully demonstrated how useful knowledge can be constructed in the form of a web-based encyclopedia by a very large, open, global community. Wiki-based technologies such as Media Wiki and T-Wiki are being used by local communities as well to collaboratively construct knowledge bases (apart from being put to altogether different uses such as schedule and project management). However, from the point of view of the present research objective, Wikipedia suffers from a significant drawback– the knowledge in a Wikipedia is still mostly buried in unstructured forms in the texts that constitute the encyclopedia (except for the rudimentary hierarchical structures in the disambiguation pages). The mechanism of hyper-linking of one text to another is too liberal to adequately structure the knowledge being encoded in the encyclopedia. What is needed is a clear separation of the structure and semantic relationships between conceptual elements of the knowledge in a precisely encoded ontology while also richly connecting both concepts and their relationships to appropriate parts of texts in several languages that define or otherwise add to the contents of the ontology. Application specific hypertext based systems are available as tools like gIBIS (a Graphical Issue Based Information System) [23] that facilitate the building and browsing of hypertext based networks in a collaborative fashion. However, their scope has been limited to capturing of informal knowledge during collaborative design.

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Thoth II, a tool for hypertext browsing, uses a large grained semantic net as its conceptual model of the domain of discourse and allows links from the semantic net nodes to point to fixed phrases in the text [25]. However, the links are syntactic in nature (i.e., exact matches of strings) [26] and structuring of the links is inadequate to prevent “the well-known lost-in-hyperspace syndrome.” Freebase, developed by Metaweb and now bought by Google, is a large collection of structured data which is harvested from many open data sources such as NNDB (Notable Names DataBase), ChefMoz, MusicBrainz, and Wikipedia [27]. The vast collection of open data (Freebase had reached a milestone of 10 million facts in November 2009) can be used for querying, building applications and uniquely identifying entities anywhere in the world but Freebase is more about structured, factual data rather than conceptual knowledge and related texts. An approach which intentionally follows the shallow semantic level of understanding is the Semantic Wiki, a wiki which entered the world when the drawbacks of Wiki (accessibility over time due to the volume and lack of structure for lean knowledge management) came to the forefront. It can be considered “the Semantic Web in small” [28]. However, it suffers from a lack of user-provided semantic annotations, resulting in a loss of efficiency. With the aim of establishing a Semantic Wiki, Semantic Media wiki [29] fulfills the purpose of addressing major problems of wikis (consistency of content, accessing knowledge and reusing knowledge) and allows mass collaboration for creating ontologies but do not support a multi-synchronous work mode [30]. Technology for creating, editing, storing and linking fine-grained annotations on text documents includes tagging (used in social bookmarking tools – Connotea, del.icio.us and Blinklist), creating sticky notes on documents and websites (mystickies, posticky, stikkit and thinkature), and combining a semantic wiki with automated text mining to try and guess what the document is about (Knewco). The use of fine grained text annotation encounters problems [32] such as the “Shyness problem” in open comments and the “Graffitti problem.” An ability to make a web page's data readable by both eyeballs and automated processes is provided by both RDFa standards and Microformats. Microformats, popularly called by some as “the lower case Semantic Web”, [33] inject semantics to the existing (x)html pages. RDFa is a more generalized and scalable solution for incorporating machine readable data along with the markup for human readable data, which benefits from the extensive power of RDF [34]. Both Microformats and RDFa have different histories and their style and future are influenced by those histories. Some

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drawbacks of using RDFa are [35] no implementations yet, need for a new form of URIs (CURIE) and breaking of CSS and (X)HTML validity. In a project, “Knowledge Web – Realizing the Semantic Web”, at AIFB, Karlsruhe, they suggest adding typed links to Wikipedia hyperlinks in order to lend them to automatic processing and query answering which overcomes the shortcomings of searching and browsing in Wikipedia in a very simple and nonintrusive way [36]. The idea in this endeavor is to introduce a system of link types that are to hyperlinks what categories are to articles. These new links differ very much from our proposal, in that they are just constrained to improving search using Wikipedia and not being related in any way to browsing the conceptual core of a knowledge domain. A project, SALT (Semantically Annotated LaTeX) at DERI, Galway, provides for a framework which helps authors transform their scientific publications into semantic documents with rhetoric annotations [37]. This system extracts the shallow metadata from the publication document and creates an associated RDF model for the document. Why not the Semantic Web? The proposed semantic web [10] comes with an elaborate set of technologies and representation languages including XML Schema [38], RDF [11], RDFS [12] and OWL [13]. However, the famous “layer cake” of these languages [39], does not offer an effective solution to either of the problems outlined above. While the XML family of languages includes members such as XLINK for linking XML elements in more complex ways than the simple hyperlink and XPATH and XPOINTER to identify and point to specific pieces of text, they have not been integrated with the semantic layers of RDF, RDFS and OWL. Nor have the behaviors of XLINK links been specified, implemented or supported in popular web browsers and other tools.

4. PROPOSED SOLUTION: SUPERLINKS The central hypothesis of the present research is that effective knowledge management needs a representation of knowledge where concepts and their relationships in the ontology are richly interconnected with pieces of text that define, explain, illustrate, compare or otherwise elaborate on the concepts. Available technology does not provide a means for effective linking of concepts in the ontology to their source texts. Such linking is extremely important to provide legitimacy to the entries in the ontology as noted above, apart from facilitating the development of the ontology itself and enabling semantic interpretation of the texts so linked. This problem is further complicated by the introduction of texts in multiple languages some of which may be translations of one another.

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4.1. What is a Superlink A Superlink is a among n different points, not just two as in the case of standard hypertext links. A point is either a piece of text (e.g., a word, phrase, proper name, clause, sentence, paragraph, section or an entire document) or a structured element in a document (e.g., an entry in a table or an item in a list) or a concept, relation, attribute or attribute value in an ontology. In comparison, in a hypertext link (i.e., the HREF attribute of the ‘A’ tag in HTML), there can be only two points (i.e., the link is always binary) and the source can be any of the above types of points but the destination of the link can only be an entire document or an approximate location in a page as already noted. In addition, a Superlink specifies the semantics of the relationship between the source and every target present in the Superlink using a typology of such semantic relations. Further, a Superlink also specified other elements of the XLINK language namely, xlink:show and xlink:actuate which specify when and how a browser should display the results of traversing a link. Since a Superlink can contain more than one target, the behavior to be exhibited by the browser when the link is clicked is ambiguous (i.e., to which target should it take the user). The design of Superlinks provides two alternative ways of choosing the correct behavior: engaging the user in an interactive dialogue using the typology of link semantics to determine which particular target point(s) may be relevant to the user, and simultaneously taking the user to all the targets in the Superlink by visiting each one and presenting a mash-up of information gathered from all the targets.

4.2. Superlink Semant ics Every target point in a Superlink has a semantic role that indicates how the source and target points are related. In addition to well-known types of conceptual relations (e.g., rdfs:SubclassOf, thesaurus:BroaderTerm, owl:ObjectProperty, etc.) a set of roles have been designed to cover the different semantic relations possible between conceptual and textual elements. These links being directional, the roles from text to concept are named CRole while those from concepts to text are named TRole. These new relations are enumerated in Table 1 below. Table 1: New Set of Semantic Types for Relations between Conceptual and Textual Elements of Knowledge. Semantic role type

TRole (concept to text)

CRole (text to concept or text)

Description

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Definition

TDef

CDef

Elaboration or description Illustration Proof Counter-example Analogy Generalization Specialization Instantiation Translation

Tel

CEl

Till TPrf TCEx TAna TGen TSpe Tins TTra

CIll CPrf CCex CAna CGen CSpe CIns CTra

Transliteration

TLit

CLit

Exercise Problem Problem solution Images Audio Video

TExe TPrb TSol TImg TAud TVid

CExe CPrb Csol CImg CAud CVid

A definition of a conceptual element in text. An elaboration or description. Examples or illustrations. A proof. A negative or counter-example. An analogy, metaphor or simile. A generalization of the concept. A specialization of the concept. A specific instance. A translation into another human language. A transliteration into another writing system. An exercise. A problem. Solution to a problem. Images of the concept. An audio recording. A video recording.

Figure 1 shows the XML encoding of a Superlink on the phrase “Indian Spices” in the text “Indian Spices are very tasty.” This link connects to four target points: a summary, examples, images and a translation in Hindi which are marked with their semantic roles of elaboration (CEl), illustration (CIll), images (CImg) and translation (CTra), respectively. The Superlink also has an attribute show=“mashup” which is a new type not present in standard XLink. This extension indicates a new behavior wherein a mash-up of the contents of the four targets is presented to the user upon clicking the Superlink.

Figure1 Error! No text of specified style in document.. XML Encoding of a Superlink on “Indian Spices” Linking to Four Target Points

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Another option for the show attribute of Superlinks is show=“dialog” in which case a user dialog is initiated to determine to which target the user prefers to navigate. An example of this behavior of Superlinks is shown in Figure 2 below.

Figure 2. Screenshot Showing Dialog Generated when User Clicked on a Superlink.

5. CAPABILITIES AND APPLICATIONS The examples shown in Figures 1 and 2 demonstrate only one of the capabilities of Superlinks, namely, the ability to generate suitable behaviors such as a dialogue or a mash-up when a user clicks on a Superlink with multiple targets. The solution presented in this paper using Superlinks is also capable of: • semantically linking concepts, relations, attributes and attribute values in an ontology (e.g, in OWL) to relevant texts; • enabling seamless navigation between conceptual structures in an ontology and related texts and documents; • linking to precise locations and spans of texts using XPointer and XPath extensions to locator specifications; • specifying the semantics of individual links using semantic role types; • enabling the development of interactive editors for constructing ontologies and knowledge bases; and

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•

linking translations and transliterations of precise pieces and spans of texts in multiple languages or encodings.

Using the above capabilities of Superlinks, several applications are being designed and built currently, including: 1. encoding and preserving traditional knowledge of India in the domains of astronomy, philosophy and traditional medicine; 2. developing Superlinked knowledge packages for teaching and elearning of difficult concepts in higher education; 3. developing Superlinked knowledge packages in vernacular languages to improve the quality of teaching in rural schools; 4. building an Integrated Development Environment (IDE) for constructing a Superlinked ontology from a set of source texts; 5. building tools for visualizing the conceptual or topic map of a text generated automatically as a view on an underlying Superlinked ontology; 6. building tools for comparative studies such as visual comparisons of the ontologies of different schools of philosophy; 7. building an automated question answering system using a Superlinked knowledge base; and 8. developing technology to generate explanations of concepts automatically by piecing together connected chunks of texts.

6. CONCLUSION AND FUTURE WORK Most work on semantic annotation of texts assumes that a good classification system such as a thesaurus, taxonomy or ontology is already available. Work on tools and technologies for developing ontologies, on the other hand, assumes that the source texts from which their conceptual knowledge is extracted can be discarded. In the work presented in this paper, we have shown how ontologies can be developed and Superlinked semantically and precisely to the source texts. Superlinks, along with their associated behaviors of user dialogues and mash-ups make it possible to design a variety of applications with newer capabilities that enrich the semantic experience of the user of a knowledge management system.

7. ACKNOWLEDGMENTS This work is supported in part by a research grant from Visvesvaraya Technological University (VTU/Aca./2009-10/A-9/11626). The author would like to acknowledge the contribution of his students Darshan N., Lavanya C., Manish Kumar M., Manisha Sinha, Neha S. Kesari, Pai Dipti G., Ranjitha C., Rishil M. Mypalli and Sandhya Francis towards the development and implementation of parts of the solution presented in this paper.

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8. REFERENCES 1.

An Overview of Document Visualization, Morse, E., http://www.itl.nist.gov/iaui/vvrg/emorse/papers/soa/DocumentVisualization.htm

2.

Annotea: an open RDF infrastructure for shared Web annotations, J Kahan, MR Koivunen, E Prud'Hommeaux, RR Swick - Computer Networks, 2002 - Elsevier

3.

BOEMIE Ontology-based Text Annotation Tool, Pavlina Fragkou, Georgios Petasis, Aris Theodorakos, Vangelis Karkaletsis and Constantine D. Spyropoulos, Greece.

4.

Definite XML Schema, Walmsley, P., Prentice Hall (2001)

5.

Design Rationale for Software Engineering: A Survey, Alex P. J. Jarczyk, Peter Löffler, Frank M. Shipman, Proceedings of the 25th Hawaii International Conference on System Sciences, 1992, Vol 2, pp. 577 – 586.

6.

Enhancing documents with annotations and machine-readable structured information using Notate, Robert Cannon and Fred Howell, www.textensor.com

7.

Freebase http://wiki.freebase.com/wiki/What_is_Freebase%3F

8.

From manual to semi-automatic semantic annotation: About ontology-based text annotation tools, M Erdmann, A Maedche, HP Schnurr, S Staab - … 2000 Workshop on Semantic Annotation and Intelligent Content, 2000 - eprints.kfupm.edu.sa

9.

gIBIS: A hypertext tool for team design deliberation, Conklin, J. and Begeman, M.L., Proceedings of the ACM conference on Hypertext, 1987.

10.

KR Requirements for Natural Language Semantics: A Critical Evaluation of Cyc, Mahesh K., Nirenburg S. and Beale S., Proceedings of KR-96 (1996)

11.

Microformats: The Next (Small) Thing on the Semantic Web? , Rohit Khare, IEEE Internet Computing, Volume 10 , Issue 1 (January 2006), Pages 6875, ISSN:1089-7801

12.

Ontogloss: an ontology-based annotation tool, F Mostowfi, F Fotouhi, A Aristar Proceedings of E-MELD Workshop on Morphosyntactic Annotation …, 2005 - emeld.org

13.

Ontological Semantics, Nirenburg, S., and Raskin, V. MIT Press (2004)

14.

Ontology based Text Annotation–OnTeA M Laclavik, M Seleng, E Gatial, Z Balogh, L Hluchy - Information Modelling and Knowledge Bases XVIII, 2007 - books.google.com, Institute ofInformatics, Slovakia.

15.

Ontology Development for Machine Translation: Ideology and Methodology, Mahesh, K. NMSU CRL Technical Report. MCCS-96-292 (1996)

16.

OpenRDF.org, Sesame RDF Database, 2006, http://www.openrdf.org/

International Conference on Digital Libraries & Knowledge Organization - 2011

17.

Organizing Knowledge: Taxonomies, Knowledge and Organizational Effectiveness, Lambe, P., Neal-Schuman Publishers (2007)

18.

OWL Web Ontology Language Overview. http://www.w3.org/TR/owl-features/.

19.

RDF Vocabulary Description Language 1.0: RDF Schema.http://www.w3.org/TR/rdfschema/.

20.

RDFa Primer, http://www.w3.org/TR/xhtml -rdfa -primer/

21.

RDFA VS. MICROFORMATS A COMPARISON OF INLINE METADATA FORMATS IN (X)HTML, Alexander Graf , Deri Innsbruck , Alexander Graf, DERI Technical Report 2007-04-10, April 2007

22.

Relational Navigation, Siderean.com, http://www.siderean.com/relational_navigation.aspx

23.

Resource Description Framework (RDF) http://www.w3.org/RDF/

24.

SALT – Semantically Annotated LaTeX, http://salt.semanticauthoring.org/index.html

25.

Semantic Classification for Practical Natural Language Processing, Mahesh, K. and Nirenburg, S., In Proceedings of the Sixth ASIS SIG/CR Classification Research Workshop: An Interdisciplinary Meeting. Pages 79-94, October 8, 1995, Chicago IL.

26.

Semantic Media Wiki, Markus Krötzsch, Denny Vr, Max Völkel, Proc. 5th International Semantic Web Conference (2006)

27.

Semantic Web Stack, Wikipedia, http://en.wikipedia.org/wiki/Semantic_Web_Stack

28.

Semantic Wikis, S. Schaffert, F. Bry, J. Baumeister, and M. Kiesel, IEEE Software, 25(4):8–11, 2008

29.

Semantics in Action. Workshop on Predicative Forms in Natural Language and Lexical Knowledge Bases, Viegas, E., Mahesh, K. and Nirenburg, S., August 1-2, 1996, Toulouse, France.

30.

SNITCH: Augmenting Hypertext documents with a Semantic Net, James Mayfield and Charles Nicholas, International Journal of Intelligent and Cooperative Information Systems 2(3):335-351, 1993

31.

The Protégé project. http://protege.stanford.edu/

32.

The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities, Berners-Lee, T., Hendler, J., and Lassila, O., The Scientific American 284: 34-43 (2001)

33.

Thoth-II: Hypertext with Explicit Semantics, George H. Collier, In Hypertext '87 Proceedings, 269-289. 1987

34.

Upper Mapping and Binding Exchange Layer (UMBEL), M. Bergman and F. Giasson, eds., Distilling Subject Concepts from OpenCyc Volume 1, Technical Report TR 08-07-16-B1, July 2008, 37 pp

International Conference on Digital Libraries & Knowledge Organization - 2011

35.

W3C Working Draft on OWL 2: Web Ontology Language, released December 2008, http://www.w3.org/TR/2008/WD-owl2-new-features-20081202/

36.

Web Information Systems Engineering - WISE 2009, Gottfried Vossen, Darrell D. E. Long, Jeffrey Xu Yu , Proc. 10th International Conference, Poznen, Poland, October 5-7, 2009

37.

What is in a Link: Foundations for Semantic Networks, Woods, W. A., In Representation and Understanding, ed. D. G. Bobrow and A. Collins. New York: Academic Press (1975)

38.

Wikipedia and the Semantic Web - The Missing Links, Markus Krötzsch, Denny Vrandecic, Max Völkel, Proceedings of Wikimania 2005 The First International Wikimedia Conference, July 2005

39.

WordNet: A lexical database for English http://www.cogsci.princeton.edu/~wn/