Using the Web to Construct Taxonomy for a Heterogeneous Community of Practice

A heterogeneous community of practice spans many disciplines, industries and professions. Members of these communities are united by common research, products and experiences but are frequently separated by specialized vocabulary and industry terms. This lack of language commonality presents a challenge to efficiently locating relevant Web based information which usually depends on the user’s knowledge of the field and ability to select suitable terms to formulate a search query. Research and practice have shown that the quality of information retrieval is significantly improved when taxonomy is employed to organize terms that describe the search domain. This paper presents an innovative, collaborative approach to building taxonomy for a particular domain, populating it with Web content and sharing it among members of the community of practice. A model is built and results and implications are discussed

Evaluating Usability of a long Query Meta search Engine

Usability is an important factor for search engine acceptance. This paper examines usability of a long query meta search engine. The engine was designed to accept and process an unlimited size query expressed in natural language. We briefly review current search engine usability research and then apply some of the common metrics to various tasks of the search and retrieval process beginning with query formulation and concluding with knowledge discovery in relevant search results. We report on users' utilization of many features offered by the engine which enhance the search experience, increase the quality of the search results and improve the usability measurements. Additionally, the implications of this study on the advancement of search engine development are discusse

Using Web Search Logs to Identify Query Classification Terms

Purpose – The work presented in this paper aims to provide an approach to classifying web logs by personal properties of users. Design/methodology/approach – The authors describe an iterative system that begins with a small set of manually labeled terms, which are used to label queries from the log. A set of background knowledge related to these labeled queries is acquired by combining web search results on these queries. This background set is used to obtain many terms that are related to the classification task. The system then ranks each of the related terms, choosing those that most fit the personal properties of the users. These terms are then used to begin the next iteration. Findings – The authors identify the difficulties of classifying web logs, by approaching this problem from a machine learning perspective. By applying the approach developed, the authors are able to show that many queries in a large query log can be classified. Research limitations/implications – Testing results in this type of classification work is difficult, as the true personal properties of web users are unknown. Evaluation of the classification results in terms of the comparison of classified queries to well known age-related sites is a direction that is currently being exploring. Practical implications – This research is background work that can be incorporated in search engines or other web-based applications, to help marketing companies and advertisers. Originality/value – This research enhances the current state of knowledge in short-text classification and query log learning. Classification schemes, Computer networks, Information retrieval, Man-machine systems, User interface

A task-oriented approach to search engine usability studies

Usability is a multi-dimensional characteristic of a computer system. This paper focuses on usability as a measurement of interaction between the user and the system. The research employs a task-oriented approach to evaluate the usability of a meta search engine. This engine encourages and accepts queries of unlimited size expressed in natural language. A variety of conventional metrics developed by academic and industrial research, including ISO standards,, are applied to the information retrieval process consisting of sequential tasks. Tasks range from formulating (long) queries to interpreting and retaining search results. Results of the evaluation and analysis of the operation log indicate that obtaining advanced search engine results can be accomplished simultaneously with enhancing the usability of the interactive process. In conclusion, we discuss implications for interactive information retrieval system design and directions for future usability research. © 2008 Academy Publisher