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Centralization vs. Decentralization Issues in Internet-based KMS: Experiences from Expertise Recommender Systems

Centralization vs. Decentralization Issues in Internet-based KMS: Experiences from Expertise Recommender Systems. Dawit Yimam, GMD-FIT.MMK & Alfred Kobsa, UCI, ICS. Outline. Background First centralized approach Alternatives - to centralize or decentralize ? DEMOIR Summary.

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Centralization vs. Decentralization Issues in Internet-based KMS: Experiences from Expertise Recommender Systems

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  1. Centralization vs. Decentralization Issues in Internet-based KMS: Experiences from Expertise Recommender Systems Dawit Yimam, GMD-FIT.MMK & Alfred Kobsa, UCI, ICS TWIST 2000

  2. Outline • Background • First centralized approach • Alternatives - to centralize or decentralize ? • DEMOIR • Summary TWIST 2000

  3. Expert Recommenders/Finders • Systems to help users in tracing human information and/or expertise sources in organizations • part of knowledge management and knowledge sharing services. • Traditionally done by manual construction and search of expertise descriptions of people, e.g., • Expert Databases (“knowledge directories”) • Personal web pages on the Web • Automatically mining implicit sources of expertise evidencefrom electronic resources of an organization and its people. Background First appr. Alternatives DEMOIR Summary TWIST 2000

  4. Characterizing Expert Finders 1. Expertise evidence/indicator source recognition and gathering 2. Expertise modeling - Expertise indicator extraction - expertise model representation 3. Expertise model deployment - query mechanisms - matching operation - output delivery/presentations - adaptation and learning operations Background First appr. Alternatives DEMOIR Summary TWIST 2000

  5. Query-time expertise modeling Background First appr. Alternatives DEMOIR Summary FIT Peoples’ and other Web Pages Glimpse WebGlimpse Web Documents Index Web Site Indexing TWIST 2000

  6. Query-time expertise modeling Background Query (Boolean) First appr. Alternatives Expert Query Interface DEMOIR Summary FIT Peoples’ and other Web Pages Glimpse WebGlimpse Web Documents Index Web Site Indexing TWIST 2000

  7. Query-time expertise modeling Search Ranked List of Experts Expertise Modeler & Tracer Expert Database (Name, URL) Background Query (Boolean) First appr. Alternatives Expert Query Interface DEMOIR Search Result (passages containing Keywords) Summary FIT Peoples’ and other Web Pages Glimpse WebGlimpse Web Documents Index Web Site Indexing TWIST 2000

  8. Query-time expertise modeling • Shortcomings: • high latency in query processing • personal sources hard to include • non-document sources (e.g. recommendation from people, social relations, etc.) hard to include • full reliance on availability of some search engine • limited exploitation of info due to lack of persistent expertise models Background First appr. Alternatives DEMOIR Summary TWIST 2000

  9. Building apps on text Indexes • Existing Web indexing systems use centralized indexes of distributed resources/collections. • Distributed Indexing needed to cope with ever growing information on Internet. • But, currently centralized global indexes (though may be distributed in a tightly coupled manner) consistently outperform decentralized indexing and query approaches. • This favors centralizing the applications to be built on them. Background First appr. Alternatives DEMOIR Summary TWIST 2000

  10. Pre-generation of Expertise Models • Alternative 1: Personal expert finding agents • Decentralized multi-agent system. • Expertise modeling as well as searching done by self-managing personal agents residing in experts’ computers (e.g. Vivacqua, 1999; Foner, 1997). • Alternative 2: Aggregated expertise modeling • Based on centralized expertise models (that are either dynamically aggregated or linked to a pre-constructed ontology) (e.g. simple versions in Kautz & Selman, 1998; Krulwich & Burkey, 1996). • Can be distributed among tightly coupled cluster of machines. Background First appr. Alternatives DEMOIR Summary TWIST 2000

  11. Personal expert finding agents Personal Expertise Model Personal Expertise Model Agent1 ----------------- ModelExpertise FindExpert Agent2 ----------------- ModelExpertise FindExpert Background First appr. Agent communication Alternatives DEMOIR Summary Personal Expertise Model Agentn ----------------- ModelExpertise FindExpert Personal Expertise Model Agent3 ----------------- ModelExpertise FindExpert TWIST 2000

  12. Aggregated Expertise Modeling Aggregated Expertise Model Expert Finding Server Background First appr. Alternatives DEMOIR Summary TWIST 2000

  13. Aggregated Expertise Modeling Aggregated Expertise Model Expert Finding Server Background First appr. local Expertise Model Alternatives Server1 DEMOIR Summary Gateway (broker) local Expertise Model Server1 L A N local Expertise Model Servern TWIST 2000

  14. Aggregated Expertise Modeling Aggregated Expertise Model Expert Finding Server Central Expertise Model Background First appr. local Expertise Model Alternatives Server1 Server1 DEMOIR Summary Gateway (broker) Gateway (broker) local Expertise Model Server1 Server1 L A N L A N local Expertise Model Servern Servern TWIST 2000

  15. Analysis Background First appr. Alternatives DEMOIR Summary TWIST 2000

  16. Analysis (contd.) Background First appr. Alternatives DEMOIR Summary TWIST 2000

  17. Hybrid Approach • Combine distributed agents with centralized expertise model server - “local-central” approach • How ? 1. Decentralized + centralized Expertise modeling • Lightweight personal agents for personal sources • Configurable gatherers for organizational resources 2. Centralized (but “distributable”) expertise information server 3. Decentralized Exploitation of expertise information (through clients) Background First appr. Alternatives DEMOIR Summary TWIST 2000

  18. DEMOIR - A Hybrid Architecture Expertise Information Space Aggregated Expertise Model Remote Expert Details Expert Models Organizational Information Resources Background First appr. Alternatives Source Wrapper1 DEMOIR EISM Summary API Expertise- indicator Source Gatherers Source Type Identifier Fusers Source Wrapper2 Clients ... Source Wrappern Ontology, Organizational structure, etc. TWIST 2000

  19. DEMOIR - A Hybrid Architecture Expertise Information Space Aggregated Expertise Model Remote Expert Details Expert Models Organizational Information Resources Background First appr. Alternatives Source Wrapper1 EISM DEMOIR API Summary Expertise- indicator Source Gatherers Source Type Identifier Fusers Source Wrapper2 Clients ... Source Wrappern Ontology, Organizational structure, etc. Gathering (decentralized Centralized) Modeling (decentralized/centralized) Exploitation (decentralized) TWIST 2000

  20. Summary/Observation • Centralized and decentralized options have their advantages and disadvantages. • Many problem domains involve both “centralizable” and “decentralizable” tasks • Challenges: • isolating such tasks and identifying the tradeoffs b/n centralizing and decentralizing their operations • If both approaches are used, how to get them work together Background First appr. Alternatives DEMOIR Summary TWIST 2000

  21. Summary/Observation • Centralization/decentralization is only one dimension of a system’s architecture. Relate to: • size/complexity of system (e.g. number of different parts, dynamism of their interaction, etc.) • heterogeneity of data and their sources • accessibility (e.g. permissions/privacy constraints, manner of use) • communication patterns among components • keep these in mind and analyze how they affect centralization/decentralization decision. Background First appr. Alternatives DEMOIR Summary TWIST 2000

  22. Summary/Observation What we did (in retrospect): 1. Identify system requirements/tasks 2. Identify and analyze centralized and decentralized alternatives of performing identified tasks • thereby identify and evaluate general centralization and decentralization factors in the problem domain. 3. Specify optimum system components as well as architecture (i.e. trying to achieve advantages and avoid disadvantages of alternatives) • aim at flexibility to allow varying degrees of centralization and/or decentralization to suit different deployment environments. Background First appr. Alternatives DEMOIR Summary TWIST 2000

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