Search (18 results, page 1 of 1)

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Abstract

This article reports the results of a study of the role of individual differences in Internet searching. The dimensions of individual differences forming the focus of the research consisted of: cognitive styles; levels of prior experience; Internet perceptions; study approaches; age; and gender. Sixty-nine Masters students searched for information on a prescribed topic using the AItaVista search engine. Results were assessed using simple binary relevance judgements. Factor analysis and multiple regression revealed interesting differences, retrieval effectiveness being linked to: male gender; low cognitive complexity; an imager (as opposed to verbalizer) cognitive style; and a number of Internet perceptions and study approaches grouped here as indicating low self-efficacy. The implications of these findings for system development and for future research are discussed.

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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

Theme

Internet

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Abstract

Offers advice on Internet search techniques and strategies. These include going straight to the information source, guessing URLs, and developing strategies for when to use subject directories (product searches, broad topics, and current events) and search engines (unique keywords, phrase searching, field searching, and limits), a multiple search strategy, and chopping off part of the URL when sites con not be found

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Abstract

Discusses the difficulties in searching the Internet, with many different tools available, and varying features associated with each one. Drawing on personal experience of teaching Internet searching, suggests presenting users with strategies for each tool, rather than detailed recipes. This strategic approach seeks to help users analyze their queries, as well as understand the basic types and principles of the different search tools to determine which might provide the most likely starting point. Suggests a preliminary analysis of questions into 4 broad types: hints are also given on finding email addresses and using complex Web browser pages

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Theme

Internet

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Abstract

People commonly experience difficulties when searching the Web, arising from an incomplete knowledge regarding their information needs, an inability to formulate accurate queries, and a low tolerance for considering the relevance of the search results. While simple and easy to use interfaces have made Web search universally accessible, they provide little assistance for people to overcome the difficulties they experience when their information needs are more complex than simple fact-verification. In human-centred Web search, the purpose of the search engine expands from a simple information retrieval engine to a decision support system. People are empowered to take an active role in the search process, with the search engine supporting them in developing a deeper understanding of their information needs, assisting them in crafting and refining their queries, and aiding them in evaluating and exploring the search results. In this chapter, recent research in this domain is outlined and discussed.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

Examines, from the perspective of professional searchers, WWW search engines that provide advanced search features and search a comprehensive abd authoritative database of Internet sites. Looks at: AltaVista, InfoSeek, Lycos, and OpenText. Gives a detailed description of each of the system, their features, how to use them and how the search engines performed on sample searches

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Abstract

The aim of the work described in this paper is to evaluate the influencing effects of query-biased summaries in web searching. For this purpose, a summarisation system has been developed, and a summary tailored to the user's query is generated automatically for each document retrieved. The system aims to provide both a better means of assessing document relevance than titles or abstracts typical of many web search result lists. Through visiting each result page at retrieval-time, the system provides the user with an idea of the current page content and thus deals with the dynamic nature of the web. To examine the effectiveness of this approach, a task-oriented, comparative evaluation between four different web retrieval systems was performed; two that use query-biased summarisation, and two that use the standard ranked titles/abstracts approach. The results from the evaluation indicate that query-biased summarisation techniques appear to be more useful and effective in helping users gauge document relevance than the traditional ranked titles/abstracts approach. The same methodology was used to compare the effectiveness of two of the web's major search engines; AltaVista and Google.

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Abstract

This research investigates how people's perceptions of information retrieval (IR) systems, their perceptions of search tasks, and their perceptions of self-efficacy influence the amount of invested mental effort (AIME) they put into using two different IR systems: a Web search engine and a library system. It also explores the impact of mental effort on an end user's search experience. To assess AIME in online searching, two experiments were conducted using these methods: Experiment 1 relied on self-reports and Experiment 2 employed the dual-task technique. In both experiments, data were collected through search transaction logs, a pre-search background questionnaire, a post-search questionnaire and an interview. Important findings are these: (1) subjects invested greater mental effort searching a library system than searching the Web; (2) subjects put little effort into Web searching because of their high sense of self-efficacy in their searching ability and their perception of the easiness of the Web; (3) subjects did not recognize that putting mental effort into searching was something needed to improve the search results; and (4) data collected from multiple sources proved to be effective for assessing mental effort in online searching.

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Abstract

Understanding search engine users' intents has been a popular study in information retrieval, which directly affects the quality of retrieved information. One of the fundamental problems in this field is to find a connection between the entity in a query and the potential intents of the users, the latter of which would further reveal important information for facilitating the users' future actions. In this article, we present a novel research method for mining the actionable intents for search users, by generating a ranked list of the potentially most informative actions based on a massive pool of action samples. We compare different search strategies and their combinations for retrieving the action pool and develop three criteria for measuring the informativeness of the selected action samples, that is, the significance of an action sample within the pool, the representativeness of an action sample for the other candidate samples, and the diverseness of an action sample with respect to the selected actions. Our experiment, based on the Action Mining (AM) query entity data set from the Actionable Knowledge Graph (AKG) task at NTCIR-13, suggests that the proposed approach is effective in generating an informative and early-satisfying ranking of potential actions for search users.

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Theme

Internet

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Theme

Internet

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Abstract

In this issue Ford, Miller and Moss utilize 68 volunteers from a population of 250 Master's students to complete on the web three search tasks with clear fact based goals and three or less facets. One task required broadening the search concepts from those given, a second provided a specific terminology for one facet but required a second facet that would require translation, and the third required general to specific transformation. The students were measured as to their performance on Entewistle's Revised Inventory of Approaches to Studying providing values for ten study variables and asked to assess their experience on the Internet, with Alta Vista, and with Boolean search. Searches were conducted on Alta Vista using Netscape Navigator 4 with participants free to choose and switch Boolean, best match or combined search modes at will while a front end script recorded all submitted searches and help access. Search related variables extracted were from Boolean only queries, best match only queries, and combined queries. Factor analyses were conducted on all variables for each search mode for each search. In task one Boolean is differentiated from best match search by sharing high loads on active interest, intention to reproduce, fear of failure, and relating ideas. The combined searcher is linked with the best match searcher with low active interest, low intention to reproduce and low fear of failure. In task 2 Boolean is differentiated from best match search by sharing high loads on intention to reproduce and low on intention to understand. Best match loads positively with intention to understand and negatively with intention to reproduce. Combined searching linked with both good and with poor time management. In task 3 the loads mimic task 1. It seems Boolean is consistently linked to a reproductive rather than a meaning seeking approach, but also with high levels of interest and fear of failure. Best match associates with the converse of these measures.

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Date

29. 7.2008 15:27:58

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Date

29. 7.2008 15:30:02

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Date

26. 1.2014 18:48:22

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Date

20. 1.2015 18:30:22