Cha-Cha: A System for Organizing Intranet Search Results

International Journal of Human-Computer Studies, 2008

Web directories organize voluminous information into hierarchical structures, helping users to quickly locate relevant information and to support decision-making. The development of existing ontologies and Web directories either relies on expert participation that may not be available or uses automatic approaches that lack precision. As more users access the Web in their native languages, better approaches to organizing and developing non-English Web directories are needed. In this paper, we have proposed a semi-automatic framework, which consists of anchor directory boosting, meta-searching, and heuristic filtering, to construct domain-specific Web directories. Using the framework, we have built a Web directory in the Spanish business (SBiz) domain. Experimental results show that the SBiz Web directory achieved significantly better recall, F-value, efficiency, and satisfaction rating than the benchmark directory. Subjects provided favorable comments on the SBiz Web directory. This research thus contributes to developing a useful framework for organizing domain-specific information on the Web and to providing empirical findings and useful insights for end-users, system developers, and researchers of Web information seeking and knowledge management.

Journal of Information Science, 2007

Context has long been considered very useful to help the user assess the actual relevance of a document. In web searching, context can help assess the relevance of a web page by showing how the page is related to other pages in the same web site, for example. Such information is very difficult to convey and visualize in a user friendly way. In this paper we present the design, implementation and evaluation of a graphical visualization tool aimed at helping users to determine the relevance of a web page by displaying the structure of the web site the page belongs to. The results of an initial evaluation suggest that this visualization technique helps the user navigate large web sites and find useful information in an effective way, without increasing the cognitive load of the user.

Computer Networks, 1999

Users of Web search engines are often forced to sift through the long ordered list of document 'snippets' returned by the engines. The IR community has explored document clustering as an alternative method of organizing retrieval results, but clustering has yet to be deployed on most major search engines. The NorthernLight search engine organizes its output into 'custom folders' based on pre-computed document labels, but does not reveal how the folders are generated or how well they correspond to users" interests. In this paper, we introduce Grouper, an interface to the results of the HuskySearch meta-search engine, which dynamically groups the search results into clusters labeled by phrases extracted from the snippets. In addition, we report on the first empirical comparison of user Web search behavior on a standard ranked-list presentation versus a clustered presentation. By analyzing HuskySearch logs, we are able to demonstrate substantial differences in the number of documents followed, and in the amount of time and effort expended by users accessing search results through these two interfaces.

IEEE Internet Computing, 1997

T he World Wide Web is a very large distributed digital information space. From its origins in 1991 as an organization-wide collaborative environment at CERN for sharing research documents in nuclear physics, the Web has grown to encompass diverse information resources: personal home pages; online digital libraries; virtual museums; product and service catalogs; government information for public dissemination; research publications; and Gopher, FTP, Usenet news, and mail servers. Some estimates suggest that the Web currently includes about 150 million pages and that this number doubles every four months.

2003

In the Web search process people often think that the hardest work is done by the search engines or by the directories which are entrusted with finding the Web pages. While this is partially true, a not less important part of the work is done by the user, who has to decide which page is relevant from the huge set of retrieved pages. In this paper we present a graphical visualisation tool aimed at helping users to determine the relevance of a Web page with respect to its structure.

Computer, 1997

A Tool for Organizing Web Information T he physical and logical differences among information sources on the Internet complicate information retrieval in several ways.

Proceedings of the American Society for …, 2005

By examining the log files from a corporate intranetsearch engine, we have analysed the actual web searching behaviour of real users in a real business environment. While building on previous research on public search engines, we apply an alternative session definition that we argue is more appropriate. Our results regarding session length, query construction and result page viewing confirm some of the findings from similar studies carried out on public search engines but further our understanding of web searching by presenting details on corporate users’ activities. In particular, we suggest that search sessions are shorter than previously suggested, search queries have fewer terms than observed for public search engines, and number of examined result pages is smaller than reported in other research. More research on how corporate intranet users search for information is needed.

2001

We developed and evaluated seven interfaces for integrating semantic category information with Web search results. List interfaces were based on the familiar ranked-listing of search results, sometimes augmented with a category name for each result. Category interfaces also showed page titles and/or category names, but re-organized the search results so that items in the same category were grouped together visually. Our user studies show that all Category interfaces were more effective than List interfaces even when lists were augmented with category names for each result. The best category performance was obtained when both category names and individual page titles were presented. Either alone is better than a list presentation, but both together provide the most effective means for allowing users to quickly examining search results. These results provide a better understanding of the perceptual and cognitive factors underlying the advantage of category groupings and provide some practical guidance to Web search interface designers.

IEEE Transactions on Knowledge and Data Engineering, 2002

Classifier for the Internet Resource Discovery (ACIRD), which uses machine learning techniques to organize and retrieve Internet documents. ACIRD consists of a knowledge acquisition process, document classifier and two-phase search engine. T he knowledge acquisition process of ACIRD automatically learns classification knowledge from classified Internet documents. The document classifier applies learned classification knowledge to classify newly collected Internet documents into one or more classes.

Information processing & management, 1996