Search (1576 results, page 1 of 79)

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Abstract

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

Date

22. 3.2009 17:49:11

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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.

Content

"Web searching is different from searching commercial IR systems. We can learn from search strategies recommended for searching IR systems, but most won't be effective for Web searching. Web searchers need strate gies that let search engines do the job they were designed to do. This article presents six new Web searching strategies that do just that."

Date

22. 9.1997 19:16:05

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Abstract

Describes how librarians at Bowling Green State University, USA, used the McKinley Search Voyeur World wide Web site to observe a sample of searches currently entered by users of the McKinley Magellan search engine, in order to try to establish how library patrons search for information. Discusses search errors revealed by this research and provides a list of tips for successful WWW searching

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Abstract

The number of non-English resources has been increasing rapidly on the Web. Although many studies have been conducted on the query logs in search engines that are primarily English-based (e.g., Excite and AltaVista), only a few of them have studied the information-seeking behavior on the Web in non-English languages. In this article, we report the analysis of the search-query logs of a search engine that focused on Chinese. Three months of search-query logs of Timway, a search engine based in Hong Kong, were collected and analyzed. Metrics on sessions, queries, search topics, and character usage are reported. N-gram analysis also has been applied to perform character-based analysis. Our analysis suggests that some characteristics identified in the search log, such as search topics and the mean number of queries per sessions, are similar to those in English search engines; however, other characteristics, such as the use of operators in query formulation, are significantly different. The analysis also shows that only a very small number of unique Chinese characters are used in search queries. We believe the findings from this study have provided some insights into further research in non-English Web searching.

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Abstract

Majority of Austrian research relevant information available an the Web these days can be indexed by web full-text search engines. But there are still several sources of valuable information, which cannot be indexed directly. One of effective ways of getting this information to end-users is using metasearch technique. For better understanding it is important to say that metasearch engine does not use its own index. It collects search results provided by other search engines, and builds a common hit list for end users. Our prototype provides access to five sources of research relevant information available an the Austrian web.

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Abstract

Because of the increasing presence of scientific publications an the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research an techniques and methods for retrieval of scientific Web publications is called for. In this article, we report an the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based an specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AlITheWeb, and AItaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AItaVista and AlITheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.

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Abstract

Enormous expanses of the Internet are unreachable with standard Web search engines. This book provides the key to finding these hidden resources by identifying how to uncover and use invisible Web resources. Mapping the invisible Web, when and how to use it, assessing the validity of the information, and the future of Web searching are topics covered in detail. Only 16 percent of Net-based information can be located using a general search engine. The other 84 percent is what is referred to as the invisible Web-made up of information stored in databases. Unlike pages on the visible Web, information in databases is generally inaccessible to the software spiders and crawlers that compile search engine indexes. As Web technology improves, more and more information is being stored in databases that feed into dynamically generated Web pages. The tips provided in this resource will ensure that those databases are exposed and Net-based research will be conducted in the most thorough and effective manner. Discusses the use of online information resources and problems caused by dynamically generated Web pages, paying special attention to information mapping, assessing the validity of information, and the future of Web searching.

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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.

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Abstract

Purpose - This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children's technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach - The study explored the Google web searching and technoliteracy of young children who are enrolled in a "preparatory classroom" or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children's web search behaviour. Findings - The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children's web searching and technoliteracy. Practical implications - The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value - This is the first study of young children's interaction with a web search engine.

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Abstract

Search engine coverage relative to the estimated size of the publicly indexable web has decreased substantially since December 97, with no engine indexing more than about 16% of the estimated size of the publicly indexable web. (Note that many queries can be satisfied with a relatively small database). Search engines are typically more likely to index sites that have more links to them (more 'popular' sites). They are also typically more likely to index US sites than non-US sites (AltaVista is an exception), and more likely to index commercial sites than educational sites. Indexing of new or modified pages byjust one of the major search engines can take months. 83% of sites contain commercial content and 6% contain scientific or educational content. Only 1.5% of sites contain pornographic content. The publicly indexable web contains an estimated 800 million pages as of February 1999, encompassing about 15 terabytes of information or about 6 terabytes of text after removing HTML tags, comments, and extra whitespace. The simple HTML "keywords" and "description" metatags are only used on the homepages of 34% of sites. Only 0.3% of sites use the Dublin Core metadata standard.

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Abstract

Internet Newsgroup archives on services such as DejaNews offer important sources of information that may not be found elsewhere online. Describes the content of the DejaNews Database which goes back to 1995 and covers more than 14,000 newsgroups. There are 2 search options: quick search and power search. Most Web search engines offer links to DejaNews, but AltaVista offers a smaller alternative and supplement to DejaNews. Reference.COM also offers a searchable archive, as well as a useful current awareness service which allows setting up multiple searches under the user profile tab

Source

Online. 22(1998) no.4, S.22-28

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Abstract

<META> tags are used to create meta-information, or information about the information in a Web site. There are many types of <META> tags, but those most relevant to indexing are the description and keyword tags. Description tags provide a short summary of the site contents that are often displayed by search engines when they list search results. Keyword tags are used to define words or phrases that someone using a search engine might use to look for relevant sites. <META> tags are of interest to indexers for two reasons. They provide a means of making your indexing business Web site more visible to those searching the Web for indexing services, and they offer indexers a potential new source of work: writing keyword and description tags for Web site developers and companies with Web sites. <META> tag writing makes good use of an indexer's ability to choose relevant key terms, and the closely related skill of abstracting: conveying the essence of a document in a sentence or two.

Issue

Beyond book indexing: how to get started in Web indexing, embedded indexing and other computer-based media. Ed. by D. Brenner u. M. Rowland.

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Abstract

This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.

Content

1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.

RSWK

Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
Bibliometrie / Semantic Web / Soziale Software

Subject

Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
Bibliometrie / Semantic Web / Soziale Software

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Abstract

Project Aristotle is a Web site clearinghouse for projects and products dealing with the automated location, categorisation, classification and organization of Web resources. Describes projects of interest to librarians and that illustrate current success in automating the cyberspace library: PHOAKS (People Helping One Anothe Know Staff; http://phoaks.com/index.html); WISE (World Wide Web Index and Search Engine; http://www.cs.ust.hk/IndexServer); WebSEEk; ET-Space (Entertainment Space; http://ai.bpa.arizona.edu/et); the Bookmark Organizer; Webmap; HyPursuit; HotPage Plus; Netscape Catalog Server; and CyberStacks

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Abstract

Directed Query Engines, an emerging class of search engine specifically designed to access distributed resources on the deep web, offer the opportunity to create inexpensive digital libraries. Already, one such engine, Distributed Explorer, has been used to select and assemble high quality information resources and incorporate them into publicly available systems for the physical sciences. By nesting Directed Query Engines so that one query launches several other engines in a cascading fashion, enormous virtual collections may soon be assembled to form a comprehensive information infrastructure for the physical sciences. Once a Directed Query Engine has been configured for a set of information resources, distributed alerts tools can provide patrons with personalized, profile-based notices of recent additions to any of the selected resources. Due to the potentially enormous size and scope of Directed Query Engine applications, consideration must be given to issues surrounding the representation of large quantities of information from multiple, heterogeneous sources.

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Abstract

This article compares search effectiveness when using query-based Internet search (via the Google search engine), directory-based search (via Yahoo), and phrase-based query reformulation-assisted search (via the Hyperindex browser) by means of a controlled, user-based experimental study. The focus was to evaluate aspects of the search process. Cognitive load was measured using a secondary digit-monitoring task to quantify the effort of the user in various search states; independent relevance judgements were employed to gauge the quality of the documents accessed during the search process and time was monitored as a function of search state. Results indicated directory-based search does not offer increased relevance over the query-based search (with or without query formulation assistance), and also takes longer. Query reformulation does significantly improve the relevance of the documents through which the user must trawl, particularly when the formulation of query terms is more difficult. However, the improvement in document relevance comes at the cost of increased search time, although this difference is quite small when the search is self-terminated. In addition, the advantage of the query reformulation seems to occur as a consequence of providing more discriminating terms rather than by increasing the length of queries

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Abstract

Examines the explosive growth and the bibliometrics of the WWW based on both analysis of over 30 GBytes of WWW pages collected by the Inktomi Web Crawler and on the use of the DEC AltaVista search engine for cocitation analysis of a set of Earth Science related WWW sites. Examines the statistical characteristics of web documents and their links, and the characteristics of highly cited web documents

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Abstract

Web search is commonly used by fact checking systems as a source of evidence for claim verification. In this work, we demonstrate that the task of retrieving pages useful for fact checking, called evidential pages, is indeed different from the task of retrieving topically relevant pages that are typically optimized by search engines; thus, it should be handled differently. We conduct a comprehensive study on the performance of retrieving evidential pages over a test collection we developed for the task of re-ranking Web pages by usefulness for fact-checking. Results show that pages (retrieved by a commercial search engine) that are topically relevant to a claim are not always useful for verifying it, and that the engine's performance in retrieving evidential pages is weakly correlated with retrieval of topically relevant pages. Additionally, we identify types of evidence in evidential pages and some linguistic cues that can help predict page usefulness. Moreover, preliminary experiments show that a retrieval model leveraging those cues has a higher performance compared to the search engine. Finally, we show that existing systems have a long way to go to support effective fact checking. To that end, our work provides insights to guide design of better future systems for the task.