Internet browsing and searching: User evaluations of category map and concept space techniques

The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Much of the current research is aimed at the developme...

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Published inJournal of the American Society for Information Science Vol. 49; no. 7; pp. 582 - 603
Main Authors Chen, Hsinchun, Houston, Andrea L., Sewell, Robin R., Schatz, Bruce R.
Format Journal Article
LanguageEnglish
Published Washington, D.C Wiley Subscription Services, Inc., A Wiley Company 15.05.1998
American Documentation Institute
Wiley Periodicals Inc
Subjects
Online AccessGet full text
ISSN0002-8231
1097-4571
DOI10.1002/(SICI)1097-4571(19980515)49:7<582::AID-ASI2>3.0.CO;2-X

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Abstract The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Much of the current research is aimed at the development and refinement of algorithms to improve browsing and searching by addressing these problems. Our research was focused on discovering whether two of the algorithms our research group has developed, a Kohonen algorithm category map for browsing, and an automatically generated concept space algorithm for searching, can help improve browsing and/or searching the Internet. Our results indicate that a Kohonen self‐organizing map (SOM)‐based algorithm can successfully categorize a large and eclectic Internet information space (the Entertainment sub‐category of Yahoo!) into manageable sub‐spaces that users can successfully navigate to locate a homepage of interest to them. The SOM algorithm worked best with browsing tasks that were very broad, and in which subjects skipped around between categories. Subjects especially liked the visual and graphical aspects of the map. Subjects who tried to do a directed search, and those that wanted to use the more familiar mental models (alphabetic or hierarchical organization) for browsing, found that the map did not work well. The results from the concept space experiment were especially encouraging. There were no significant differences among the precision measures for the set of documents identified by subject‐suggested terms, thesaurus‐suggested terms, and the combination of subject‐ and thesaurus‐suggested terms. The recall measures indicated that the combination of subject‐ and thesaurus‐suggested terms exhibited significantly better recall than subject‐suggested terms alone. Furthermore, analysis of the home pages indicated that there was limited overlap between the homepages retrieved by the subject‐suggested and thesaurus‐suggested terms. Since the retrieved homepages for the most part were different, this suggests that a user can enhance a keyword‐based search by using an automatically generated concept space. Subjects especially liked the level of control that they could exert over the search, and the fact that the terms suggested by the thesaurus were “real” (i.e., originating in the homepages) and therefore guaranteed to have retrieval success. © 1998 John Wiley & Sons, Inc.
AbstractList The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Much of the current research is aimed at the development and refinement of algorithms to improve browsing and searching by addressing these problems. Our research was focused on discovering whether two of the algorithms our research group has developed, a Kohonen algorithm category map for browsing, and an automatically generated concept space algorithm for searching, can help improve browsing and/or searching the Internet. Our results indicate that a Kohonen self‐organizing map (SOM)‐based algorithm can successfully categorize a large and eclectic Internet information space (the Entertainment sub‐category of Yahoo!) into manageable sub‐spaces that users can successfully navigate to locate a homepage of interest to them. The SOM algorithm worked best with browsing tasks that were very broad, and in which subjects skipped around between categories. Subjects especially liked the visual and graphical aspects of the map. Subjects who tried to do a directed search, and those that wanted to use the more familiar mental models (alphabetic or hierarchical organization) for browsing, found that the map did not work well. The results from the concept space experiment were especially encouraging. There were no significant differences among the precision measures for the set of documents identified by subject‐suggested terms, thesaurus‐suggested terms, and the combination of subject‐ and thesaurus‐suggested terms. The recall measures indicated that the combination of subject‐ and thesaurus‐suggested terms exhibited significantly better recall than subject‐suggested terms alone. Furthermore, analysis of the home pages indicated that there was limited overlap between the homepages retrieved by the subject‐suggested and thesaurus‐suggested terms. Since the retrieved homepages for the most part were different, this suggests that a user can enhance a keyword‐based search by using an automatically generated concept space. Subjects especially liked the level of control that they could exert over the search, and the fact that the terms suggested by the thesaurus were “real” (i.e., originating in the homepages) and therefore guaranteed to have retrieval success. © 1998 John Wiley & Sons, Inc.
The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Two of these algorithms, a Kohonen algorithm category map for browsing and an automatically generated concept space algorithm for searching, are investigated if they can help improve browsing and/or searching the Internet.
Contribution to a special topic issue devoted to artificial intelligence techniques for emerging information systems applications. Reports research to discover whether a Kohonen algorithm category map for browsing, and an automatically generated concept space algorithm for searching, can help improve browsing and/or searching the Internet. Reviews the current status of Internet browsing services and discusses the implementation of the SOM-based method to categorise a set of about 110,000 entertainment-related WWW homepages. Reviews the current status of Internet searching and the thesaurus or concept space approach to the vocabulary differences problem. Discusses the implementation of an automatically generated thesaurus on the same set of WWW homepages. Presents the experimental design and the qualitative results of the browsing task experiment. Presents the quantitative results and the qualitative results of the searching task experiment. (Original abstract - amended)
This study found that a Kohonen self-organizing map (SOM) algorithm for browsing can categorize a large and eclectic Internet-information space into manageable sub-spaces that users can navigate to find relevant home pages. An automatically generated concept-space algorithm for searching was shown to enhance keyword-based Internet searching. Contains 65 references. (PEN)
The Internet provides an exceptional testbed for devel oping algorithms that can improve browsing and search ing large information spaces. Browsing and searching tasks are susceptible to problems of information over load and vocabulary differences. Much of the current research is aimed at the development and refinement of algorithms to improve browsing and searching by ad dressing these problems. Our research was focused on discovering whether two of the algorithms our research group has developed, a Kohonen algorithm category map for browsing, and an automatically generated con cept space algorithm for searching, can help improve browsing and/or searching the Internet. Our results indi cate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclec tic Internet information space (the Entertainment sub category of Yahoo!) into manageable sub-spaces that users can successfully navigate to locate a homepage of interest to them. The SOM algorithm worked best with browsing tasks that were very broad, and in which sub jects skipped around between categories. Subjects es pecially liked the visual and graphical aspects of the map. Subjects who tried to do a directed search, and those that wanted to use the more familiar mental mod els (alphabetic or hierarchical organization) for brows ing, found that the map did not work well. The results from the concept space experiment were especially en couraging. There were no significant differences among the precision measures for the set of documents identi fied by subject-suggested terms, thesaurus-suggested terms, and the combination of subject- and thesaurus- suggested terms. The recall measures indicated that the combination of subject- and thesaurus-suggested terms exhibited significantly better recall than subject-sug gested terms alone. Furthermore, analysis of the homepages indicated that there was limited overlap between the homepages retrieved by the subject-suggested and thesaurus-suggested terms. Since the retrieved home- pages for the most part were different, this suggests that a user can enhance a keyword-based search by using an automatically generated concept space. Subjects es pecially liked the level of control that they could exert over the search, and the fact that the terms suggested by the thesaurus were "real" (i.e., originating in the homepages) and therefore guaranteed to have retrieval success.
The development and refinement of algorithms to improve browsing and searching by addressing information overload and vocabulary differences are discussed. Whether 2 particular algorithms can help improve browsing and searching the Internet is studied. The results indicate that a Kohenen self-organizing map-based algorithm can successfully categorize a large and eclectic Internet information space into manageable sub-spaces that users can successfully navigate to locate a homepage of interest to them. A study of an automatically generated concept space algorithm for searching was especially encouraging. Subjects especially like the level of control they could exert over such a search.
Author Chen, Hsinchun
Houston, Andrea L.
Schatz, Bruce R.
Sewell, Robin R.
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Bellamy (10.1002/(SICI)1097-4571(19980515)49:7<582::AID-ASI2>3.0.CO;2-X-BIB1.4) 1989; 80
Ekmekcioglu (10.1002/(SICI)1097-4571(19980515)49:7<582::AID-ASI2>3.0.CO;2-X-BIB7.5) 1992; 18
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References_xml – reference: DeBra, P., & Post, R. (1994). Information retrieval in the World-Wide Web: Making client-based searching feasible. Computer Networks and ISDN Systems, 27(2), Nov. 1995, 183-192.
– reference: Piternick, A. B. (1984). Searching vocabularies: A developing category of online search tools. Online Review, 8(5), 441-449.
– reference: Frenkel, K. A. (1991). The human genome project and informatics. Communications of the ACM, 34(11), 41-51.
– reference: Knapp, S. D. (1984). Creating BRS/TERM, a vocabulary database for searchers. Database, 7(4), 70-75.
– reference: Green, R. (1995). Topical relevance relationships. I. Why topic matching fails. Journal of the American Society for Information Science, 46, 646-653.
– reference: Bowman, C. M. (1994). The Harvest information discovery and access system. Computer Networks and ISDN Systems, 28(1-2), Dec. 1995, 119-125.
– reference: Green, R., & Bean, C. A. (1995). Topical relevance relationships. II. An exploratory study and preliminary typology. Journal of the American Society for Information Science, 46, 654-662.
– reference: Chen, P. L., Martinez, J., Ng, D. T., & Schatz, B. R. (1997a). A concept space approach to addressing the vocabulary problem in scientific information retrieval: An experiment on the Worm Community System. Journal of the American Society for Information Science, 48, 157-170.
– reference: Nadis, S. (1996). Computation cracks semantic barrier between databases. Science, 272, 1419.
– reference: Crouch, C. J. (1990). An approach to the automatic construction of global thesauri. Information Processing and Management, 26(5), 629-640.
– reference: Bowman, Cm., Danzig, P. B., Manber, U., & Schwartz, F. (1994). Scalable internet resource discovery: Research problems and approaches. Communications of the ACM, 37(8), 98-107.
– reference: Peat, H. J., & Willett, P. (1991). The limitations of term co-occurrence data for query expansion in document retrieval systems. Journal of the American Society for Information Science, 42, 378-383.
– reference: Chen, H. (1994). Collaborative systems: Solving the vocabulary problem. IEEE Computer, 27(5) [Special issue on computer-supported cooperative work (CSCW)], 58-66.
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Snippet The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching...
This study found that a Kohonen self-organizing map (SOM) algorithm for browsing can categorize a large and eclectic Internet-information space into manageable...
The Internet provides an exceptional testbed for devel oping algorithms that can improve browsing and search ing large information spaces. Browsing and...
Contribution to a special topic issue devoted to artificial intelligence techniques for emerging information systems applications. Reports research to discover...
The development and refinement of algorithms to improve browsing and searching by addressing information overload and vocabulary differences are discussed....
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SubjectTerms Algorithms
Browsing
Category maps
Concept Mapping
Concept spaces
Digital libraries
Experiments
Home Pages
Information Overload
Information Retrieval
Information Seeking
Internet
Internet service providers
Keywords
Kohonen (Teuvo)
Navigation (Information Systems)
Online information retrieval
Query expansion
Recall
Relevance (Information Retrieval)
Science
Search algorithms
Search Strategies
Searching
Self Organizing Maps
Semantics
Space
Thesauri
Visual aspects
Title Internet browsing and searching: User evaluations of category map and concept space techniques
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