Case Based Reasoning and Storytelling Integration - Semantic Scholar

Case Based Reasoning and Storytelling Integration: a Way to Acquire and Represent Social and Domain Knowledge in the Design of Knowledge Management Systems Stefania Bandini1 , Federica Petraglia1 , and Fabio Sartori1 Research Center on Complex Systems and Artificial Intelligence Department of Computer Science, Systems and Communication (DISCo) University of Milan - Bicocca via Bicocca degli Arcimboldi, 8 20126 - Milan (Italy) tel +39 02 64487857 - fax +39 02 64487839 {bandini, sartori, federica}@disco.unimib.it

Abstract. Knowledge Management has been always considered as a problem of acquiring, representing and using information and knowledge about problem solving methods. Anyway, the complexity reached by organizations over the last years has deeply changed the role of Knowledge Management. Today, it is not possible to take care of knowledge involved in decision making processes without taking care of social context where it is produced. In this paper a conceptual and computational framework to acquire and represent both social and know-how knowledge is presented based on an integration of case–based techniques and storytelling methodology. The result is the possibility to exploit a unique knowledge structure, named Complex Knowledge Structure (CKS) to model knowledge about a decisional process to solve a problem (i.e. the story) from both the problem solving and communication among people involved viewpoints.

1

Introduction

Since the first years, the development of Knowledge Management Systems (KMS) has been considered as a problem of capturing, organizing, and retrieving information, through knowledge acquisition and representation sessions on different kinds of knowledge sources (e.g. domain experts, documents, programs and so on). This conception of Knowledge Management is strongly oriented to the design of computer–based systems that are able to reproduce the problem–solving strategy of human people. Knowledge cannot be seen as a passive entity, composed of facts that can be stored, retrieved, and disseminated, but the context in which these facts were originally embedded, and the new and often quite different contexts in which they will be used should be also taken into account. In particular the capability

to analyze and exploit the social context where knowledge is generated becomes a crucial aspect in the design and implementation of modern KMS. Since the end of 1980’s, several works (see e.g. [12] [13] [7]) have pointed out the importance of social context on learning, knowledge generation and sharing processes. In these approaches, it emerges the vision of knowledge as a complex entity, that is the result of the interaction between the individuals involved and the environment where they live and work. This situated approach (see e.g. [11] [5]), that is inspired by Vigostskij (see e.g. [14]), highlights that knowledge is characterized by the nature of the specific situation in which it is produced. A typical example of such situations is given by Communities of practice [15], where knowledge production and dissemination is the result of a possibly complex negotiation and reification process among their members (see e.g. [3]). In this context, knowledge becomes an active entity: a piece of knowledge cannot be considered a fact that is used to generate other facts, but the result of a social process that possibly generates other social processes. Thus, a modern approach to Knowledge Management should focus on the development of methodologies and tools for properly representing social interactions among people involved in knowledge creation. In this paper, we present a conceptual and computational framework for the acquisition and representation of knowledge involved in complex decision making processes, both from the domain know–how and social interchanges between experts perspective. This approach is based on the integration of storytelling and case–based reasoning [10] methodologies: the former allows to manage a decision making process like a story that describes problem characteristics and what kind of communications among people and problem solution strategies can be applied to solve it; the latter is a very useful and efficient mean to compare stories (i.e. cases) finding solutions to new problems by reusing past experiences. The result is a Complex Knowledge Structure (CKS) that allows to describe at the same time all the aspects of a problem, its solution and how the solution has been found, and that can be compared to other CKSs in order to improve knowledge formalization and sharing within organizations. Contexts where Communities of Practice act are the natural targets of a CKS: the negotiation–reification process conducted by CoP members to solve critical situations can be profitably represented taking care not only of domain knowledge devoted to find a solution, but also the social relationships among people involved. In this paper, we present Complex Knowledge Structures from the conceptual point of view: after a brief introduction to storytelling for motivating its adoption in the CKS definition, given in section 2, the paper describes CKSs as useful means to support CoP in the generation and reuse of negotiation and reification processes in section 3. To better explain aims of CKS the intuitive example of dinner preparation is used. Finally, conclusions and future work are briefly pointed out.

2

Storytelling as a Knowledge Management Conceptual Framework

“Storytelling is a fundamental form of human communication [...] We often think in story form, speak in story form, and bring meaning to our lives through story. Storytelling, in most common everyday form, is giving a narrative account of an event, an experience, or any other happening [...] It is this basic knowledge of an event that allows and inspires us to tell about it. What generally happens when we tell a story from our life is that we increase our working knowledge of ourselves because we discover deeper meaning in our lives through the process of reflecting and putting the events, experience, and feelings that we have lived into oral expression.” [1] Storytelling is a short narration through which an individual describes an experience on a specific theme. In this way, the human being is motivated to focus the attention on his/her own knowledge about the specific theme that is the subject of narration [6]. A storytelling allows to bring order and meaning to the event to be told, with benefits for both who tells and who listens it. Within organizations, this method can be considered an effective way to treasure the knowledge that is produced from the daily working activities. For example, Roth and Kleiner [9] have analyzed how the adoption of storytelling allows an organization to: – be more conscious about its overall knowledge; – share knowledge among all the people involved in its generation; – treasure and disseminate new knowledge originated by the sharing of different stories. The adoption of storytelling can promote the development of new professional contexts where different professionals collaborate to solve common problems, share experiences, explicit and implicit assumptions and understandings in order to improve the global capability of the organization to transform, create and distribute knowledge. In this sense, Knowledge Management can profitably exploit the storytelling as a way to: – make explicit the individual experiences, skills and competencies; – promote the negotiation processes through dialogues among people involved; – support the reification of new knowledge in order to make it available for the future; – help newcomers in the learning process about his/her job through the analysis of the problem–solving strategies and social context represented by the stories. Doing so, according to [1], Knowledge Management can become “a way to better understand the past and the present and the way to leave a personal legacy for the future”. For this reason, the development of tools and methodologies for acquiring and representing properly knowledge involved in complex human activities also from

the social context point of view is becoming a very important aspect of Knowledge Management. In the following sections, the Complex Knowledge Structure will be presented as an example of how this KM aspect can be captured into a conceptual framework based on the definition of Complex Knowledge Structures. CKS has been thought and designed to support the knowledge acquisition, representation and use in organizational contexts where Communities of practice emerge and operate.

3

Complex Knowledge Structures

CoPs are groups of people sharing expertise and passion about a topic and interacting on an ongoing basis to deepen their learning in this domain [15]. One of the most interesting feature of CoPs is their informal nature: a CoP is typically transversal with respect to the formal structure of an Organization. This means that members of a CoP usually belongs to different Business Units of a Company, different departments of a University and so on. Each member is bounded to others by common interests, friendship and other social relationships different from the normal day by day working activities. A CoP is an excellent vehicle for the circulation of ideas, information and knowledge within Organizations, thus they should be able to encourage the development of CoPs. When a new problem arises that a CoP member should solve, an immediate and deep communication process starts, involving all the people belonging to the CoP and eventually other CoPs. The process is typically iterative, ending when the problem is solved and generating new knowledge that will be useful in the future. This process can be called negotiation-reification and represents the way how CoPs are able to manage their core competencies, characterizing themselves as important centers for finding innovative solutions to a wide variety of problems in a lot of domains. The term Complex Knowledge Structure (CKS) has been coined to indicate a way to represent all the features of the negotiation-reification process inside CoPs. The reason for considering “Complex” the knowledge structures related to a negotiation and reification process is that a CKS is not only a representation of a simple piece of knowledge owned by CoP members, but also of the social relationships established among the people belonging to the Community during its generation: Definition 1 (Complex Knowledge Structure) A Complex Knowledge Structure is a mean to acquire and represent in a uniform fashion both the domain and social knowledge involved in a CoP negotiation–reification process. Domain knowledge concerns the problem–solving activity, while social knowledge is related to what kind of communications and relationships are established among CoP members in order to solve critical situations. Domain and social knowledge involved in a negotiation–reification process should describe three main features of it:

WHAT-Node HOW-Node WHY-Node

WHAT-Rel HOW-Rel WHY-Rel

Fig. 1. The representation of CKSs in the CKS–Net Framework

1. WHAT are the main elements of a negotiation–reification process, i.e. what is the structure of a problem to be solved in terms of entities that are considered by CoPs’ members and relationships are established among them? 2. WHY CoPs’ members work on the structure defined by the previous point, i.e. what are the goals of the negotiation–reification process? 3. HOW CoPs’ members exploit their experience to modify or change the problem structure according to the wished aims? In this sense, a Complex Knowledge Structure can be considered as a mean to describe the narration of a story represented by a negotiation–reification process. 3.1

Representing CKSs in the CKS–Net Framework

A CKS is represented (see Figure 1) as a graph with three kinds of nodes and relationships among them: WHAT-Nodes are used to describe entities involved in the problem description. They could be a representation of people or pieces of knowledge. HOWNodes are exploited to identify what kind of entities helps in the definition of a solution to a problem. Finally, WHY-Nodes can explain the result of the solution application to the problem. Relationships among these nodes are used to express in a completely way the negotiation-reification process. WHAT-Rels bind a WHAT-Node to another one and represent a social or knowledge link between them in the description of a problem. HOW-Rels are established between a WHAT-Node and a HOW-Node, in order to point out that the HOW-Node can be linked to a WHAT-Node representing a part of the problem description. Finally, a WHY-Rel can be drawn from a HOW-Node to a WHY-Node in order to highlight what kind of aim could be reach exploiting the solution or from a WHY-Node to another one to make clear some causal relation between an aim of the problem solution and a possible side-effect. Relationships are generic and

labelled: this means they can be utilized to describe CoPs and, in particular, the negotiation-reification process, from different point of views. For instance, WHAT-Rels could be used to illustrate a negotiation–reification process in terms of: – Social relationships among CoP members. In this case, each WHAT-Node bounded by a WHAT-Rel represents a person involved in the negotiationreification process, and the WHAT-Rel explains what kind of interaction is established between them (e.g. asks to, helps, doesn’t speak to, etcetera); – Know-How relationships among the parts of a product or the phases of a production process. In this case, each WHAT-Node represents a product or production process component and a relationship between them represents a piece of core-knowledge owned by the whole CoP(e.g. is a, is made of, is followed by, etcetera); – Interactions among different CoPs. In this case, each node is a specific CoP, and the relation between them specifies what kind of cooperation exists when they have to solve a common problem. A CKS devoted to represent interactions among different CoPs will be similar to the CKS for the analysis of social relationships among CoP members, but it will typically contain a smaller number of nodes and relationships. To show how a CKS can be constructed starting from a very simple and intuitive problem: the organization of dinner. This relatively trivial case study allows to take care of all the issues reported above. From the social relationship point of view, a dinner can be viewed as a net of persons and relationships among them. From the know-how relationship stand point the dinner can be considered as a set of different meals, each one prepared according to precise rules. Finally, a dinner can also be exploited to analyze interactions among different people involved in its configuration: for instance, it is possible to think that a person is devoted to prepare meat, another one cakes, etcetera. 3.2

Social Relationships

Philip and Tamara are married. They have no sons, but a lot of friends. A day, Tamara decides to invite them for a dinner: unfortunately, many friends are already busy, thus the dinner becomes a very restricted event. People accepting the invitation are Albert, Anne, Tom, Greta, Jane, Sheila, Tracy and Elvis. Albert and Anne were schoolmates of Philip and Tamara and, as well as the them, they are married. Anne and Tom are colleagues: they are friends, but Tom doesn’t know Anne’s husband Albert. Greta is Tom’s wife: they married in a while after they knew, a very simple ceremony with few guests. Thus, Greta doesn’t know anyone. Jane is single and she is a very close friend of Albert as well as Tracy. Elvis only knows Philip and Tamara and Jane. Finally, Sheila is a friend of Philip and Tamara they knew during a trip. She is very nice but shy and she doesn’t know anyone. Philip and Tamara would be happy if Sheila will have a good time. Moreover, they wish Sheila knows Elvis.

Sheila

HAS

Anne IS MARRIED

Albert

Good Time KNOWS

IS FRIEND Tom

IS FRIEND

IS FRIEND Elvis

Tracy IS NEAR IS MARRIED Jane Greta IS FRIEND

Elvis

Fig. 2. The representation of social relationships among people invited to Philip and Tamara dinner. Sheila is a HOW–Node, since she doesn’t know anyone and Philip and Tamara wish she has a good time. The solution adopted is to place Jane near Sheila, in order to make possible that Sheila knows Elvis. Moreover, Jane has a many direct or indirect connections to other nodes.

The situation depicted above is shown in Figure 2, where Sheila has been drawn as a HOW-Node. In fact, the solution adopted by Philip and Tamara to reach their two aims is to place Jane near Sheila during the dinner. This is due to the following reasons: Jane is a friend of Albert, that is a friend of Tracy and married to Anne. Thus, Jane has also the possibility to be introduced to Anne and Albert friends; Jane is the only person that knows Elvis; with respect to Albert, who could be the other candidate to sit near Sheila, Jane is a female. Since Sheila is very shy, it will probably be simpler for her to talk to another woman rather than a man.

3.3

Know-How Relationships

Tamara has just solved the problem of finding a place to Sheila, but she has a new critical situation to think about: the men´ u configuration. She would organize a four-course Italian style dinner: a cold appetizers, made of asparagus flan and ham roll´e; pasta alla Norma, that is macaroni with mozzarella, pomodoro, aubergine and basil; entr´ec´ote with mixed salads and oven-roasted potatoes; jam tart with mixed fresh fruit; coffee and tea. Tamara has not much time. Thus, she has chosen courses characterized by ingredients easy to be bought and simple in preparation, light but with a pleasant taste too. Figure 3 shows the representation of the dinner men´ u as a Complex Knowledge Structure. It is possible to notice how the decision to offer a jam tart has been guided by the lack of time: in fact, Tamara had to decide between a Sacher Cake, but it was to difficult and long to be prepared.

IS Asparagus Flan

Appetizers

IS FOLLOWED BY

IS Ham Rollè

Macaroni

MADE OF Simple Preparation

Aubergine

MADE OF Pasta alla Norma

Pomodoro

MADE OF

IS FOLLOWED BY

MADE OF Basil Entrècòte TO OBTAIN

Oven-roasted Potatoes TOGETHER WITH Mixed Salads IS FOLLOWED BY IS CHOSEN Sacher Cake Jam tart MADE OF MADE OF

Cream Short Pastry

MADE OF

Fresh Fruit

Fig. 3. The representation of know-how relationships owned by Tamara about the dinner men´ u. In particular, Tamara decided to prepare a jam tart instead of a Saker Cake due to lack of time. Thus the jam tart node is a HOW-Node

3.4

Interactions

The dinner day is arrived. Tamara has just come back home from the office and she has to prepare the decided men´ u. Unfortunately, she notices that asparaguses were not bought. Thus, she cannot prepare the asparagus flan. As a first solution to this problem, Tamara decides to present ham roll´e as unique appetizer. But she immediately discards this possibility. Then, she thinks to ask her mother how to prepare an asparagus flan without asparaguses: “Use aubergines instead of asparaguses” - the mother says - “Do you have aubergines, don’t you? Aubergines are good and you can prepare a very good cream using them. Substitute the asparagus flan with an aubergine one in your appetizer list and you’ll be able to preserve the pleasant taste of your dinner.” . Tamara thanks her mother for the important suggestion and comes back to work on the men´ u. The diagram shown in Figure 4 contains three HOW-Node: mother and aubergine. The first node represents how Tamara solves her problem (i.e. what can I prepare instead of asparagus flan?), the second one is the solution to the effective problem represented by the CKS (i.e. in what way can lacking asparaguses be substituted?). The third HOW-Node is a representation of the initial solution found by Tamara, that was to offer a unique appetizer to invited people. This solution, that make the ham roll´e change from the WHAT-Node to the HOW-Node status, would have produced the Poor Appetizers WHY-Node, that is the representation of a drawback rather than a benefit. The Pleasant

Suggestion Mother LACKS

TO OBTAIN ASK IS SUBSTITUTED BY

Asparaguses

Aubergine

CAUSES

IS MADE OF

Appetizers

Flan

PREPARE ONLY IS

Pleasant Taste

Ham Rollè TO OBTAIN

Poor Appetizers

Fig. 4. The representation of interaction relationships between two people to solve a problem. Tamara’s mother suggests to her daughter to substitute asparaguses with aubergines in order to prepare the flan. Doing so, Tamara will be able to preserve consistency and pleasant taste of appetizers. There is a causal relationship between the WHY–Node Suggestion and the WHY–Node Pleasant Taste since the second one is a direct consequence of the first one.

Taste WHY-Node is the final state of the CKS: there is a direct consequence between the solution to Tamara’s problem and to the problem represented by the CKS: asparaguses have been substituted by aubergines because Tamara asked her mother what she had to do. This consequentiality between the two WHYNodes is highlighted by the presence of a causal relationship starting from the Suggestion node and ending into the Pleasant Taste node.

4

Comparing Stories: Unsolved Complex Knowledge Structures

This representation can be used in a Case-Based Reasoning framework to compare negotiation–reification processes from both the social and know-how standpoints: let’s suppose that a new problem arises that should be tackled by a CoP. CoP members starts a negotiation to find a solution, maybe exploiting past experiences that could have been stored in another CKS. In this way, it could be possible to establish analogies between a solved CKS and an unsolved (UCKS) one, that is a CKS without HOW–Nodes and HOW–Rels, and use the lessons learned in the past to solve a current critical situation. To better explain how, let us tell another story about a dinner configuration. After the first successful dinner, Tamara decides to invite her colleagues for a lunch on a Sunday. Invited people are completely different, but Tamara has

Jim Maggie

Good Time Wayne IS MARRIED

IS FRIEND

IS FRIEND Asia IS NEAR IS FRIEND

Vanessa Part A

Aaron Jim

Good Time

Vanessa

Part B

Fig. 5. An Unsolved Complex Knowledge Structure representing the new problem of Tamara in organizing a lunch with her colleagues (Part A) and the solution obtained by comparing the new situation with the past dinner (Part B).

a similar problem: how to make Jim, a newcomers who doesn’t know anyone but Tamara, be happy during the lunch? The representation of this problem is shown by the Unsolved Complex Knowledge Structure in part A of Figure 5: the situation is very similar to the previous one (see Figure 2). Jim, as Sheila, is an isolated node in the problem description. The aim of a possible solution is to create a link to the Good Time WHY-Node: to do this, it is important to notice that Wayne and Vanessa are the only critical nodes together with the unique WHY-Node of the UCKS. Indeed, Vanessa and Wayne are similar to Jane and Albert in Figure 2. Thus, it is possible to state that: Vanessa and Jane are equivalent; Wayne and Albert too. It is reasonable to suppose that the application of the old solution to the new problem could be a good step. Thus, Jim is transformed into a HOW-Node through the creation of a IS NEAR link from Vanessa to him, as shown in the part B of Figure 5. Through a generalization of the simple problem solving method above it has been possible to obtain an effective retrieval algorithm for Complex Knowledge Structures, based on the identification of the so called critical nodes (e.g. Vanessa, Jim, Wayne and Albert) in the UCKS and CKS descriptions, acting on the set (rather than one as in the example) of all the past Complex Knowledge Structures. The definition of criticality of nodes in the Complex Knowledge Structures has been inspired by the concept of centrality of nodes in the Social Network Analysis [8]: Further details about the algorithm are out of paper scope and they can be found in [2].

5

Conclusions and Future Work

This paper has presented a way to describe social and domain knowledge relationships involved in a negotiation reification process within organizational contexts where communities of practice are active, based on the Complex Knowledge Structure artifact. In order to favorite the storage of all the knowledge involved in the decision making process of a CoP, the following choices have been taken: a Complex Knowledge Structure is a graph, with three kinds of nodes and three kinds of relationships among them; a WHAT–Node is used to identify an entity necessary to describe the problem; a HOW–Node allows to identify a step of the problem solving strategy; a WHY-Node is used to define a goal of the negotiation-reification process; a WHAT Relationship is used to describe the nature of link between two WHAT–Nodes; a HOW Relationship is used to illustrate a step in the reasoning process to solve a new problem; a WHY Relationship is used to show the benefits of a problem solving step represented by a How relationship. The use of the CKS construct in the case-based reasoning context allows to design effective Knowledge Management Systems to support CoPs in their negotiation–reification process. According to the conceptual model described in this paper, a prototype of CKS–Net has been designed and implemented exploiting the Java techology, as a first step in the development of a complete software platform for supporting CoPs: to this aim, the adoption of Java will allow to build a unique version of the software capable to run under many operating systems. Figure 6 shows a screenshot of the CKS–Net prototype, where a CKS representing a story made of three WHAT–Nodes, two HOW–Nodes and two WHY– Nodes has been drawn as well as three WHAT–Rels, two HOW–Rels and three WHY–Rels.

Fig. 6. A screenshot of the developed prototype of the CKS–Net framework.

The development of this prototype has allowed to test the effectiveness of the CKS–Net framework in the context of the P–Truck Tuning project [4], a collaboration between the University of Milan–Bicocca and the Business Unit Truck of Pirelli to support experts in the analysis and solution of process anomalies that can arise during the manufacturing of truck tires (i.e. the tuning problem): The work has shown that the representation of expert decision making processes as comparable stories described by CKSs and the retrieval algorithm described could be a good approach, but this should be investigated at a deeper level of detail. In fact, the tuning problem is characterized by few possible anomalies, representable by CKSs with few nodes and relationships. In such situations, the polynomial complexity of the retrieval algorithm allows to obtain an initial solution to the problem in relative short time period. Anyway, the CKS–Net framework must be necessarily tested on larger CKS–Bases than the P–Truck Tuning one. Moreover, CKS–Net presents some other drawbacks that could represent possible limitations to its employment in solving general configuration problems: – the syntax is not simple to be managed. The adoption of three sets of nodes and relationships could result difficult to be understood. Despite of the prototype development with its graphical user interface, differences among nodes and relationships and how to describe them into a CKS could be not simple; – the definition of the conceptual model of the framework has been given in a specific domain. Thus, it is possible that it cannot be applicable to other kinds of domains; – from the negotiation–reification process point of view, the unification of problem description, solution and outcome into a story is indeed useful for fully understanding how core knowledge is produced inside CoPs. Anyway, this could be not true outside of the CoP context, where negotiation typically doesn’t exist. The analysis of the three points above will be subject of future work to verify its applicability in building supporting systems for knowledge sharing and learning.

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