Search (6 results, page 1 of 1)

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Abstract

Tips zur Suche, u.a. zur Produktsuche im Web

Source

Online. 24(2000) no.3, S.61-66

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Abstract

Surfing the World Wide Web used to be cool, dude, real cool. But things have gotten hot - so hot that finding something useful an the Web is no longer cool. It is suffocating Web searchers in the smoke and debris of mountain-sized lists of hits, decisions about which search engines they should use, whether they will get lost in the dizzying maze of a subject directory, use the right syntax for the search engine at hand, enter keywords that are likely to retrieve hits an the topics they have in mind, or enlist a browser that has sufficient functionality to display the most promising hits. When it comes to Web searching, in a few short years we have gone from the cool image of surfing the Web into the frying pan of searching the Web. We can turn down the heat by rethinking what Web searchers are doing and introduce some order into the chaos. Web search strategies that are tool-based-oriented to specific Web searching tools such as search en gines, subject directories, and meta search engines-have been widely promoted, and these strategies are just not working. It is time to dissect what Web searching tools expect from searchers and adjust our search strategies to these new tools. This discussion offers Web searchers help in the form of search strategies that are based an strategies that librarians have been using for a long time to search commercial information retrieval systems like Dialog, NEXIS, Wilsonline, FirstSearch, and Data-Star.

Date

22. 9.1997 19:16:05

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Content

Key Features - Importantly, the book enables readers to develop strategies which will continue to be useful despite the rapidly-evolving state of the Internet and Internet technologies - it is not about technological `tricks'. - Enables readers to be aware of and compensate for bias and errors which are ubiquitous an the Internet. - Provides contemporary information an the deficiencies in web skills of novice users as well as practical techniques for teaching such users. The Authors Dr Alison Stacey works at the Learning Resource Centre, Cambridge Regional College. Dr Adrian Stacey, formerly based at Cambridge University, is a software programmer. Readership The book is aimed at a wide range of librarians and other information professionals who need to retrieve information from the Internet efficiently, to evaluate their confidence in the information they retrieve and/or to train others to use the Internet. It is primarily aimed at intermediate to advanced users of the Internet. Contents Fundamentals of information retrieval from the Internet - why learn web searching technique; types of information requests; patterns for information retrieval; leveraging the technology: Search term choice: pinpointing information an the web - why choose queries carefully; making search terms work together; how to pick search terms; finding the 'unfindable': Blas an the Internet - importance of bias; sources of bias; usergenerated bias: selecting information with which you already agree; assessing and compensating for bias; case studies: Query reformulation and longer term strategies - how to interact with your search engine; foraging for information; long term information retrieval: using the Internet to find trends; automating searches: how to make your machine do your work: Assessing the quality of results- how to assess and ensure quality: The novice user and teaching internet skills - novice users and their problems with the web; case study: research in a college library; interpreting 'second hand' web information.

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Abstract

A study of the "real world" Web information searching behavior of 206 college students over a 10-month period showed that, contrary to expectations, the users adopted a more passive or browsing approach to Web information searching and became more eclectic in their selection of Web hosts as they gained experience. The study used a longitudinal transaction log analysis of the URLs accessed during 5,431 user days of Web information searching to detect changes in information searching behavior associated with increased experience of using the Web. The findings have implications for the design of future Web information retrieval tools

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Abstract

Conventional wisdom holds that queries to information retrieval systems will yield more relevant results if they contain multiple topic-related terms and use Boolean and phrase operators to enhance interpretation. Although studies have shown that the users of Web-based search engines typically enter short, term-based queries and rarely use search operators, little information exists concerning the effects of term and operator usage on the relevancy of search results. In this study, search engine users formulated queries on eight search topics. Each query was submitted to the user-specified search engine, and relevancy ratings for the retrieved pages were assigned. Expert-formulated queries were also submitted and provided a basis for comparing relevancy ratings across search engines. Data analysis based on our research model of the term and operator factors affecting relevancy was then conducted. The results show that the difference in the number of terms between expert and nonexpert searches, the percentage of matching terms between those searches, and the erroneous use of nonsupported operators in nonexpert searches explain most of the variation in the relevancy of search results. These findings highlight the need for designing search engine interfaces that provide greater support in the areas of term selection and operator usage

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Abstract

Subject content analysis of Web query terms is essential to understand Web searching interests. Such analysis includes exploring search topics and observing changes in their frequency distributions with time. To provide a basis for in-depth analysis of users' search interests on a larger scale, this article presents a query categorization approach to automatically classifying Web query terms into broad subject categories. Because a query is short in length and simple in structure, its intended subject(s) of search is difficult to judge. Our approach, therefore, combines the search processes of real-world search engines to obtain highly ranked Web documents based on each unknown query term. These documents are used to extract cooccurring terms and to create a feature set. An effective ranking function has also been developed to find the most appropriate categories. Three search engine logs in Taiwan were collected and tested. They contained over 5 million queries from different periods of time. The achieved performance is quite encouraging compared with that of human categorization. The experimental results demonstrate that the approach is efficient in dealing with large numbers of queries and adaptable to the dynamic Web environment. Through good integration of human and machine efforts, the frequency distributions of subject categories in response to changes in users' search interests can be systematically observed in real time. The approach has also shown potential for use in various information retrieval applications, and provides a basis for further Web searching studies.