Modelling Document Usage in Competitive Intelligence Process

1. Modelling Document Usage in Competitive Intelligence Process L. A. Akanbi B. S. Afolabi A. David E. R. Adagunodo Transition from Observation to Knowledge to Intelligence TOKI2014

2. Outline of the Presentation • Competitive Intelligence • Document Annotation • Document Usage Model • Model Evaluation • Conclusion Transition from Observation to Knowledge to Intelligence TOKI2014

3. Competitive Intelligence Competitive Intelligence is a process that involves: • gathering, analysis and processing of environmental information • Assisting strategic decision making (Trigo et al., 2007; Dishman and Calof, 2008) • The process of information gathering is legal and ethical (SCIP, 2012) • The environment could be external or internal to the organization. Transition from Observation to Knowledge to Intelligence TOKI2014

4. Stages in Competitive Intelligence Process • Identification and specification of decision problem • Transformation of decision problem into information search problem • Identification and validation of sources • Collection and validation of necessary information Transition from Observation to Knowledge to Intelligence TOKI2014

5. Stages in Competitive Intelligence Process cont’d • Processing and calculating of necessary indicators for decision making • Interpretation of indicators • Decision making for the resolution of identified problem (Chen et al., 2002; Odumuyiwa and David, 2008) Transition from Observation to Knowledge to Intelligence TOKI2014

6. Identification of Decision Problem (DP) Competitive Intelligence Process < represented as > Transformation of DP into Information Search Problem Terms in the documents Identification of Relevant Sources of Information < collect from> Documents Sources Collection of Relevant Information Analysis of Collected Information to extract indicators for decision making Interpretation of Indicators Decision Making Transition from Observation to Knowledge to Intelligence TOKI2014

7. Identification of Decision Problem (DP) Competitive Intelligence Process < represented as > Transformation of DP into Information Search Problem Terms in the documents Identification of Relevant Sources of Information Documents Sources < collect from> Collection of Relevant Information Usage descriptors (U, P, D & E) < represented as > Analysis of Collected Information to extract indicators for decision making Interpretation of Indicators Decision Making Transition from Observation to Knowledge to Intelligence TOKI2014

8. Document Annotation • Annotation can be seen as simply information about the document, assigned by a process or human, after the original creation of the document (Ogilvie, 2010) Transition from Observation to Knowledge to Intelligence TOKI2014

9. Some Applications of Document Annotation • AMIE- Annotation Model for Information Exchange – (Robert and David, 2006) • The model was reported to have been conceived with the objective of information sharing and reuse • The use of annotation process as an indexing approach that allows the users to identify and regroup documents or their sub-elements under a particular use context was employed in Maghreb and David (2008) • AMTEA -Annotation Model and Tools for Economic Actors– (Okunoye et al. (2010) • proposed the use of annotation representation as Attribute-Value-Pair (AVP) as a medium of capturing EI actors’ interpretation to document of interest. Transition from Observation to Knowledge to Intelligence TOKI2014

10. Problem Statement All search activities for information is associated with a decision problem. • Existing techniques for integrating context into document index are based on inference methods using statistical or linguistic methods. • These methods cannot capture the usage of information by the end-user. Transition from Observation to Knowledge to Intelligence TOKI2014

11. Document Usage Model • The document usage is modelled as a function of the following attributes: • DU = f(U, P, D, R) where: DU = Document usage U = User P = decision Problem D = Document representation R = document degree of relevance to the resolution of decision problem Transition from Observation to Knowledge to Intelligence TOKI2014

12. Document Usage Model The User attribute (U) is composed of the following values: U = {id, status, estab} where: id = a unique identity allocated to the user during the course of registering to use the system status = the current position of the user in the establishment or organization. estab = the users’ establishment information such as type of establishment (private or public) and name of the establishment. Transition from Observation to Knowledge to Intelligence TOKI2014

13. Document Usage Model Taking cue from Bouaka (2004), we describe the decision problem P as: P = {Obj, Signal, Hyp} where: Obj = the stake object attribute. Signal = the stake signal i.e. the level of the user’s knowledge about the decision problem. Hyp = the stake hypothesis i.e. what the establishment stand to gain or lose. Transition from Observation to Knowledge to Intelligence TOKI2014

14. Document Usage Model The attribute D of the DU is also formally define as: D = {id, title, abs} where: id = the unique identity of the document. This is automatically assigned by the system. title = title of the document abs = document abstract or summary. Transition from Observation to Knowledge to Intelligence TOKI2014

15. Document Usage Model The attribute R of the DU is document’s degree of relevance to the resolution of the decision problem. It s a function of the following attributes: R = f(UR, UY, NP) where: UR = User’s rating of document’s relevance to decision problem UY = User’s number of years in the establishment NP = Number of similar problems handled in the past Transition from Observation to Knowledge to Intelligence TOKI2014

16. Document Usage Model where is the users of the system is the document’s degree of relevance to decision problem (DP) is the terms from the DP description is the terms from the documents is the number of users in the system is the number of terms in the document space Transition from Observation to Knowledge to Intelligence TOKI2014

17. Document Usage Model • Items and are used to generate value added information • Items and are used to generate the usage index (UI). Transition from Observation to Knowledge to Intelligence TOKI2014

18. Model Evaluation • Vector Space Model was used to represent the document collection in the document space • Calculate the similarity between Decision Problem and key-term based document index • Calculate the similarity between decision problem and usage based document index • Compare the two results Transition from Observation to Knowledge to Intelligence TOKI2014

19. Calculating the Similarity between Decision Problem and Documents where: j = 1 …….. n (n= number of document in the document collection space). t = the number of terms in the vector space. dj = jth document vector in the document space P = decision problem transform to document vector in the document collection space wij = the weight of term i in document j. wi,q= the weight of term i in the query q (i.e. the decision problem). Transition from Observation to Knowledge to Intelligence TOKI2014

20. Sample Document and DP • d1 = AMIE: An annotation model for information research • d2 = AMTEA: Tool for Creating and Exploiting Annotations in the Context of Economic Intelligence (Competitive Intelligence) • d3 = What Is a "Document"? • d4 = CI Spider: a tool for competitive intelligence on the Web • d5 = Dynamic Knowledge Capitalization through Annotation among Economic Intelligence Actors in a Collaborative Environment • d6 = Design and Development of a Model for Generating and Exploiting Annotation in the Context of Economic Intelligence • dp = Development of model and system to create usage descriptors for documents. Then writing of Doctorate thesis on the model and the system. Transition from Observation to Knowledge to Intelligence TOKI2014

21. Document Index based on key terms • d1 = AMIE: annotation model information research • d2 = AMTEA: Tool Creating Exploiting Annotations Context Economic Intelligence Competitive Intelligence • d3 = Document • d4 = CI Spider tool competitive intelligence Web • d5 = Dynamic Knowledge Capitalization Annotation Economic Intelligence Actors Collaborative Environment • d6 = Design Development Model Generating Exploiting Annotation Context Economic Intelligence Transition from Observation to Knowledge to Intelligence TOKI2014

22. Document Index in Vector Space Transition from Observation to Knowledge to Intelligence TOKI2014

23. Document Usage Index in Vector Space Transition from Observation to Knowledge to Intelligence TOKI2014

24. Similarity between Decision Problem and Documents Transition from Observation to Knowledge to Intelligence TOKI2014

25. In Graphical Form Transition from Observation to Knowledge to Intelligence TOKI2014

26. Result Analysis • Threshold is usually set (e.g. 0.3) for documents to be considered relevant to queries. • Documents d4 and d5 will not be considered relevant to the query Transition from Observation to Knowledge to Intelligence TOKI2014

27. Conclusion • The IR component of the CI process is very crucial to speedy and easy resolution of DPs. • This work sought to keep track of what documents have been used for and incorporate it into the document representation scheme to enhance the quality of IR stage of the CI process. • The document usage model presented is used to preserve the effort, the decision makers put to discover relevant documents for the resolution of DPs Transition from Observation to Knowledge to Intelligence TOKI2014

28. Thanks for Listening Transition from Observation to Knowledge to Intelligence TOKI2014

29. Transition from Observation to Knowledge to Intelligence TOKI2014

30. A sample information retrieval (search) analysis Ph.D. Qualifying Exam

31. A sample information retrieval (search) analysis Ph.D. Qualifying Exam

32. Some causes of the perceived noise in the information retrieved • indexing is by keyterms generated from the documents only • terms usually have different concept • users’ inability to properly and correctly translate their needs into query • users' lack of adequate knowledge about how the system functions Ph.D. Qualifying Exam

33. ? (a, b) ? (a, b) ? ( b) ? (a, b) Demand Users a) Decision maker b) Watcher Information World Information Base Selection Cognitive Process - Observation - Elementary abstraction - Reasoning - Creativity mapping Value Added Information Decision Results Analysis Interpretation Competitive Intelligent System Architecture (Source: Thiery and David, 2002) Proposed Transition from Observation to Knowledge to Intelligence TOKI2014

34. DP descriptors User Information Documents Documents Documents Request Information World Document usage index Information Base Document index Value Added Information Decision Results Architecture of the Proposed System Selection Mapping Interpretation Analysis Existing Transition from Observation to Knowledge to Intelligence TOKI2014

35. Research Questions • Is it possible to model document usage computationally? • Can the document usage model be incorporated into document representation for modern information retrieval system (IRS)? • Can documents usage model enhance accessibility to documents required for the resolution of decision problem? Transition from Observation to Knowledge to Intelligence TOKI2014

36. Research Theory and Philosophy • The Philosophy of this work is derived from the gratification theory (Fiske, 1990) • Given the history of the usage of a document in addition to author’s defined key terms, there is the likelihood to increase the rate of accessibility to the documents in the nearest future. Transition from Observation to Knowledge to Intelligence TOKI2014

37. Research Aim • The aim of this work is to create a computing environment in term of software that will allow for creation and exploration of document usage Transition from Observation to Knowledge to Intelligence TOKI2014

38. Research Justification • Representing document with terms generated from the document itself and previous usage will enhance the rate of accessibility to the document • Thereby reducing the amount of effort that would be required by users to identify documents that are relevant to their information needs Transition from Observation to Knowledge to Intelligence TOKI2014

39. Research Objectives The specific objectives are to: i. formulate a model that augments document index with usage ii. design a system based on the model formulated in (i) iii. implement the system designed in (ii) and iv. evaluate the system Transition from Observation to Knowledge to Intelligence TOKI2014

40. Literature Review • Indexing by latent semantic analysis (Deerwesteret al. 1990) involves the use of Singular Value Decomposition (SVD) to analyse the term-document matrix. Modeling the underlying term-to-document association patterns is the key in this approach • Context Based Indexing in Search Engines using Ontology (Gupta and Sharma, 2010) involves the use of context repository, thesaurus and ontology repository to build the document index Transition from Observation to Knowledge to Intelligence TOKI2014

41. Literature Review • Okunoye and Uwadia(2011) Designed and Developed a Model for Generating and Exploiting Annotation in the Context of Economic Intelligence Proposed representation of annotation as attribute value pair rather than as atomic object, to allow the user to carry out annotation on documents with their specified attribute and value. Other related works are here Transition from Observation to Knowledge to Intelligence TOKI2014

42. Research Methodology • Document usage model was created with the use of Attribute Value Pair technique of document annotation and Vector Space Model of Information Retrieval • A system that integrates document usage with document index based on (i) was produced with the use of Unified Modelling Language (UML 2.0) • The prototype of the system was implemented with the use of PhPand MySqltechnology • The system was evaluated with the use similarity measure (i.e. Euclidean distance) between sample decision problems and documents • Form A Transition from Observation to Knowledge to Intelligence TOKI2014

43. Publications • L. A. Akanbi and E. R. Adagunodo (2013) A framework for linking Documents with its usage within the Context of Competitive Intelligence. 9th International Society for Knowledge Organization Conference. Paris, France. 10 -13 October 2013.- PUBLISHED • L. A. Akanbi, B. S. Afolabi, E. R. Adagunodo and A. David. Modelling Document Usage in Competitive Intelligence Process. TOKI Conference (2014) University of Lagos. Nigeria. 20 – 22 August 2014 -ACCEPTED Transition from Observation to Knowledge to Intelligence TOKI2014

44. Other Information Transition from Observation to Knowledge to Intelligence TOKI2014

45. Statement of the Problem • The process of identifying useful documents that contribute to the resolution of decision problems are often time-consuming and uneconomical. • Existing search systems do not incorporate document usage into document indexing. • To enhance accessibility to documents, there is the need for a system to augment document index with document usage. Hence, this study. • Back Transition from Observation to Knowledge to Intelligence TOKI2014

46. Research Methodology • Attribute Value Pair, a document annotation technique will be used to formulate a model that augments document index with document usage. A software system will be designed based on the model formulated with the use of Unified Modelling Language (UML 2.0). The prototype of the system designed will be implemented with PhP and MySQL technology. To evaluate the performance of the system, data on document usage will be collected through questionnaire administration and guided interview. The data will be collected from twenty (20) selected postgraduate students (M.Sc. and Ph.D.) in various departments in the faculty of Technology who are at different stages of their thesis. Similarity measure based on Euclidean distance between identified relevant documents by the respondents and their decision problems (i.e. research problems) will be used to evaluate the system. • Back Transition from Observation to Knowledge to Intelligence TOKI2014

47. Identification of Decision Problem (DP) Transformation of DP into Information Search Problem < represented as > Identification of Relevant Sources of Information Documents Sources Terms in the documents < collect from> Collection of Relevant Information < represented as > Usage descriptors (U, P, D & E) Analysis of Collected Information to extract indicators for decision making Interpretation of Indicators Decision Making CI Process incorporating Document Usage Transition from Observation to Knowledge to Intelligence TOKI2014

48. TR H L MD 1 µ(EL) 0 1 2 3 4 5 Number of Years Transition from Observation to Knowledge to Intelligence TOKI2014

49. NR SR R VR 1 µ(EL) 0 1 2 3 4 5 User’s Rating of Document Relevance to DP Resolution Transition from Observation to Knowledge to Intelligence TOKI2014

50. S VS H M VH Number of Similar Problem Solved 1 µ(NSP) 0 1 2 3 4 5 Number of Similar Problem handled in the past Transition from Observation to Knowledge to Intelligence TOKI2014