Conference proceeding
Scalability of Findability: Effective and Efficient IR Operations in Large Information Networks
SIGIR 2010: PROCEEDINGS OF THE 33RD ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH DEVELOPMENT IN INFORMATION RETRIEVAL, pp 74-81
01 Jan 2010
Abstract
It is crucial to study basic principles that support adaptive and scalable retrieval functions in large networked environments such as the Web, where information is distributed among dynamic systems. We conducted experiments on decentralized IR operations on various scales of information networks and analyzed effectiveness, efficiency, and scalability of various search methods. Results showed network structure, i.e., how distributed systems connect to one another, is crucial for retrieval performance. Relying on partial indexes of distributed systems, some level of network clustering enabled very efficient and effective discovery of relevant information in large scale networks. For a given network clustering level, search time was well explained by a poly-logarithmic relation to network size (i.e., the number of distributed systems), indicating a high scalability potential for searching in a growing information space. In addition, network clustering only involved local self-organization and required no global control clustering time remained roughly constant across the various scales of networks.
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Details
- Title
- Scalability of Findability: Effective and Efficient IR Operations in Large Information Networks
- Creators
- Weimao Ke - University of North Carolina at Chapel HillJaved Mostafa - University of North Carolina at Chapel Hill
- Contributors
- H H Chen (Editor)E N Efthimiadis (Editor)J Savoy (Editor)F Crestani (Editor)S MarchandMaillet (Editor)
- Publication Details
- SIGIR 2010: PROCEEDINGS OF THE 33RD ANNUAL INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH DEVELOPMENT IN INFORMATION RETRIEVAL, pp 74-81
- Publisher
- Assoc Computing Machinery
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000286904100011
- Scopus ID
- 2-s2.0-77956046077
- Other Identifier
- 991020546416304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems