Search (92 results, page 1 of 5)

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Content

Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.

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Abstract

SOSIG (Social Science Information Gateway) aims to provide a trusted source of selected, high quality Internet information for researchers and practitioners in the social sciences, business and law. This article tracks the the development of the gateway since its inception in 1994, describes the current features and looks at some of the associated research and development areas that are taking place around the service including the automatic classification of Web resources and experiments with multilingual thesauri

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Abstract

This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of "information practice" and other related concepts such as "use", "activity", and "behavior" largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.

Date

20. 4.2012 13:22:37

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Abstract

Despite improvements in their capabilities, search engines still fail to provide users with only relevant results. One reason is that most search engines implement a "one size fits all" approach that ignores personal preferences when retrieving the results of a user's query. Recent studies (Smyth, 2010) have elaborated the importance of personalizing search results and have proposed integrating recommender system methods for enhancing results using contextual and extrinsic information that might indicate the user's actual needs. In this article, we review recommender system methods used for personalizing and improving search results and examine the effect of two such methods that are merged for this purpose. One method is based on collaborative users' knowledge; the second integrates information from the user's social network. We propose new methods for collaborative-and social-based search and demonstrate that each of these methods, when separately applied, produce more accurate search results than does a purely keyword-based search engine (referred to as "standard search engine"), where the social search engine is more accurate than is the collaborative one. However, separately applied, these methods do not produce a sufficient number of results (low coverage). Nevertheless, merging these methods with those implemented by standard search engines overcomes the low-coverage problem and produces personalized results for users that display significantly more accurate results while also providing sufficient coverage than do standard search engines. The improvement, however, is significant only for topics for which the diversity of terms used for queries among users is low.

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Abstract

Social phenomena happen, and the historians follow. So it goes with Google, the latest star shooting through the universe of trend-setting businesses. This company has even entered our popular lexicon: as many note, "Google" has moved beyond noun to verb, becoming an action which most tech-savvy citizens at the turn of the twenty-first century recognize and in fact do, on a daily basis. It's this wide societal impact that fascinated authors David Vise and Mark Malseed, who came to the book with well-established reputations in investigative reporting. Vise authored the bestselling The Bureau and the Mole, and Malseed contributed significantly to two Bob Woodward books, Bush at War and Plan of Attack. The kind of voluminous research and behind-the-scenes insight in which both writers specialize, and on which their earlier books rested, comes through in The Google Story. The strength of the book comes from its command of many small details, and its focus on the human side of the Google story, as opposed to the merely academic one. Some may prefer a dryer, more analytic approach to Google's impact on the Internet, like The Search or books that tilt more heavily towards bits and bytes on the spectrum between technology and business, like The Singularity is Near. Those wanting to understand the motivations and personal growth of founders Larry Page and Sergey Brin and CEO Eric Schmidt, however, will enjoy this book. Vise and Malseed interviewed over 150 people, including numerous Google employees, Wall Street analysts, Stanford professors, venture capitalists, even Larry Page's Cub Scout leader, and their comprehensiveness shows. As the narrative unfolds, readers learn how Google grew out of the intellectually fertile and not particularly directed friendship between Page and Brin; how the founders attempted to peddle early versions of their search technology to different Silicon Valley firms for $1 million; how Larry and Sergey celebrated their first investor's check with breakfast at Burger King; how the pair initially housed their company in a Palo Alto office, then eventually moved to a futuristic campus dubbed the "Googleplex"; how the company found its financial footing through keyword-targeted Web ads; how various products like Google News, Froogle, and others were cooked up by an inventive staff; how Brin and Page proved their mettle as tough businessmen through negotiations with AOL Europe and their controversial IPO process, among other instances; and how the company's vision for itself continues to grow, such as geographic expansion to China and cooperation with Craig Venter on the Human Genome Project. Like the company it profiles, The Google Story is a bit of a wild ride, and fun, too. Its first appendix lists 23 "tips" which readers can use to get more utility out of Google. The second contains the intelligence test which Google Research offers to prospective job applicants, and shows the sometimes zany methods of this most unusual business. Through it all, Vise and Malseed synthesize a variety of fascinating anecdotes and speculation about Google, and readers seeking a first draft of the history of the company will enjoy an easy read.

Date

3. 5.1997 8:44:22

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Content

Inhalt: Acknowledgments; Abstract; Zusammenfassung; Contents; List of Figures; List of Tables; List of Acronyms; Chapter 1 Introduction ; 1.1 Research Questions; 1.2 Thesis Outline; Part I Fundamentals ; Chapter 2 Information Retrieval for Young Users ; 2.1 Basics of Information Retrieval; 2.1.1 Architecture of an IR System; 2.1.2 Relevance Ranking; 2.1.3 Search User Interfaces; 2.1.4 Targeted Search Engines; 2.2 Aspects of Child Development Relevant for Information Retrieval Tasks; 2.2.1 Human Cognitive Development; 2.2.2 Information Processing Theory; 2.2.3 Psychosocial Development 2.3 User Studies and Evaluation2.3.1 Methods in User Studies; 2.3.2 Types of Evaluation; 2.3.3 Evaluation with Children; 2.4 Discussion; Chapter 3 State of the Art ; 3.1 Children's Information-Seeking Behaviour; 3.1.1 Querying Behaviour; 3.1.2 Search Strategy; 3.1.3 Navigation Style; 3.1.4 User Interface; 3.1.5 Relevance Judgement; 3.2 Existing Algorithms and User Interface Concepts for Children; 3.2.1 Query; 3.2.2 Content; 3.2.3 Ranking; 3.2.4 Search Result Visualisation; 3.3 Existing Information Retrieval Systems for Children; 3.3.1 Digital Book Libraries; 3.3.2 Web Search Engines 3.4 Summary and DiscussionPart II Studying Open Issues ; Chapter 4 Usability of Existing Search Engines for Young Users ; 4.1 Assessment Criteria; 4.1.1 Criteria for Matching the Motor Skills; 4.1.2 Criteria for Matching the Cognitive Skills; 4.2 Results; 4.2.1 Conformance with Motor Skills; 4.2.2 Conformance with the Cognitive Skills; 4.2.3 Presentation of Search Results; 4.2.4 Browsing versus Searching; 4.2.5 Navigational Style; 4.3 Summary and Discussion; Chapter 5 Large-scale Analysis of Children's Queries and Search Interactions; 5.1 Dataset; 5.2 Results; 5.3 Summary and Discussion Chapter 6 Differences in Usability and Perception of Targeted Web Search Engines between Children and Adults 6.1 Related Work; 6.2 User Study; 6.3 Study Results; 6.4 Summary and Discussion; Part III Tackling the Challenges ; Chapter 7 Search User Interface Design for Children ; 7.1 Conceptual Challenges and Possible Solutions; 7.2 Knowledge Journey Design; 7.3 Evaluation; 7.3.1 Study Design; 7.3.2 Study Results; 7.4 Voice-Controlled Search: Initial Study; 7.4.1 User Study; 7.5 Summary and Discussion; Chapter 8 Addressing User Diversity ; 8.1 Evolving Search User Interface 8.1.1 Mapping Function8.1.2 Evolving Skills; 8.1.3 Detection of User Abilities; 8.1.4 Design Concepts; 8.2 Adaptation of a Search User Interface towards User Needs; 8.2.1 Design & Implementation; 8.2.2 Search Input; 8.2.3 Result Output; 8.2.4 General Properties; 8.2.5 Configuration and Further Details; 8.3 Evaluation; 8.3.1 Study Design; 8.3.2 Study Results; 8.3.3 Preferred UI Settings; 8.3.4 User satisfaction; 8.4 Knowledge Journey Exhibit; 8.4.1 Hardware; 8.4.2 Frontend; 8.4.3 Backend; 8.5 Summary and Discussion; Chapter 9 Supporting Visual Searchers in Processing Search Results 9.1 Related Work

Date

1. 2.2016 18:25:22

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Abstract

This paper presents a new approach to query expansion in search engines through the use of general non-topical terms (NTTs) and domain-specific semi-topical terms (STTs). NTTs and STTs can be used in conjunction with topical terms (TTs) to improve precision in retrieval results. In Phase I, 20 topical queries in two domains (Health and the Social Sciences) were carried out in Google and from the results of the queries, 800 pages were textually analysed. Of 1442 NTTs and STTs identified, 15% were shared between the two domains; 62% were NTTs and 38% were STTs; and approximately 64% occurred before while 36% occurred after their respective topical terms (TTs). Findings of Phase II showed that query expansion through NTTs (or STTs) particularly in the 'exact title' and URL search options resulted in more precise and manageable results. Statistically significant differences were found between Health and the Social Sciences vis-à-vis keyword and 'exact phrase' search results; however there were no significant differences in exact title and URL search results. The ratio of exact phrase, exact title, and URL search result frequencies to keyword search result frequencies also showed statistically significant differences between the two domains. Our findings suggest that web searching could be greatly enhanced combining NTTs (and STTs) with TTs in an initial query. Additionally, search results would improve if queries are restricted to the exact title or URL search options. Finally, we suggest the development and implementation of knowledge-based lists of NTTs (and STTs) by both general and specialized search engines to aid query expansion.

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Source

Behavioral and social sciences librarian. 15(1996) no.1, S.53-56

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Abstract

When I interned at Google last summer after getting my MSI degree, I worked on projects for the Book Search and Google Scholar teams. I didn't know it at the time, but in completing my research over the course of the summer, I would become the resident expert on how universities were approaching Google Scholar as a research tool and how they were implementing Scholar on their library websites. Now working at an academic library, I seized a recent opportunity to sit down with Anurag Acharya, Google Scholar's founding engineer, to delve a little deeper into how Scholar features are developed and prioritized, what Scholar's scope and aims are, and where the product is headed. -Tracey Hughes, GIS Coordinator, Social Sciences & Humanities Library, University of California San Diego

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Abstract

"Web Search Engine Research", edited by Dirk Lewandowski, provides an understanding of Web search engines from the unique perspective of Library and Information Science. The book explores a range of topics including retrieval effectiveness, user satisfaction, the evaluation of search interfaces, the impact of search on society, reliability of search results, query log analysis, user guidance in the search process, and the influence of search engine optimization (SEO) on results quality. While research in computer science has mainly focused on technical aspects of search engines, LIS research is centred on users' behaviour when using search engines and how this interaction can be evaluated. LIS research provides a unique perspective in intermediating between the technical aspects, user aspects and their impact on their role in knowledge acquisition. This book is directly relevant to researchers and practitioners in library and information science, computer science, including Web researchers.

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Abstract

Recent technological progress in computer science, Web technologies, and constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Web search has significantly evolved in recent years. In the beginning, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, new web search engines support aggregated search over a number of vertices, and blend different types of documents (e.g., images, videos) in their search results. New search engines employ advanced techniques involving machine learning, computational linguistics and psychology, user interaction and modeling, information visualization, Web engineering, artificial intelligence, distributed systems, social networks, statistical analysis, semantic analysis, and technologies over query sessions. Documents no longer exist on their own; they are connected to other documents, they are associated with users and their position in a social network, and they can be mapped onto a variety of ontologies. Similarly, retrieval tasks have become more interactive and are solidly embedded in a user's geospatial, social, and historical context. It is conjectured that new breakthroughs in information retrieval will not come from smarter algorithms that better exploit existing information sources, but from new retrieval algorithms that can intelligently use and combine new sources of contextual metadata.
With the rapid growth of web-based applications, such as search engines, Facebook, and Twitter, the development of effective and personalized information retrieval techniques and of user interfaces is essential. The amount of shared information and of social networks has also considerably grown, requiring metadata for new sources of information, like Wikipedia and ODP. These metadata have to provide classification information for a wide range of topics, as well as for social networking sites like Twitter, and Facebook, each of which provides additional preferences, tagging information and social contexts. Due to the explosion of social networks and other metadata sources, it is an opportune time to identify ways to exploit such metadata in IR tasks such as user modeling, query understanding, and personalization, to name a few. Although the use of traditional metadata such as html text, web page titles, and anchor text is fairly well-understood, the use of category information, user behavior data, and geographical information is just beginning to be studied. This book is intended for scientists and decision-makers who wish to gain working knowledge about search engines in order to evaluate available solutions and to dialogue with software and data providers.

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Abstract

Exploiting context information in a web search engine helps fine-tuning web services and applications to deliver custom-made information to end users. While context, including user and environment information, cannot be exploited efficiently in the wired Internet interaction type, it is becoming accessible with the mobile web where users have an intimate relationship with their handsets. In this type of interaction, context plays a significant role enhancing information search and therefore, allowing a search engine to detect relevant content in all digital forms and formats. This chapter proposes a context model and an architecture that promote integration of context information for individuals and social communities to add value to their interaction with the mobile web. The architecture relies on efficient knowledge management of multimedia resources for a wide range of applications and web services. The research is illustrated with a corporate case study showing how efficient context integration improves usability of a mobile search engine.

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Date

22. 6.2002 19:40:22

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Source

Computers in libraries. 19(1999) no.5, S.22-28

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Date

25. 8.2005 17:42:22

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Source

Ariadne. 1999, no.22

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Date

7. 6.2008 16:22:20

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Abstract

Ambiguities in Web search tool (more commonly known as "search engine") terminology are problematic when conducting precise, replicable research or when teaching others to use search tools. Standardized terminology would enable Web searchers to be aware of subtle differences between Web search tools and the implications of these for searching. A categorization and nomenclature for standardized classifications of different aspects of Web search tools is proposed, and advantages and disadvantages of using tools in each category are discussed

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Abstract

Over the last years, research and industry players have become increasingly interested in analyzing opinions and sentiments expressed on the social media web for product marketing and business intelligence. In order to adapt to this need search engines not only have to be able to retrieve lists of documents but to directly access, analyze, and interpret topics and opinions. This article covers an intermediate phase of the ongoing industrial research project 'DoXa' aiming at developing a semantic opinion and sentiment mining search engine for the French language. The DoXa search engine enables topic related opinion and sentiment extraction beyond positive and negative polarity using rich linguistic resources. Centering the work on two distinct business use cases, the authors analyze both unstructured Web 2.0 contents (e.g., blogs and forums) and structured questionnaire data sets. The focus is on discovering hidden patterns in the data. To this end, the authors present work in progress on opinion topic relation extraction and visual analytics, linguistic resource construction as well as the combination of OLAP technology with semantic search.

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Abstract

Web search engines act as gatekeepers when people search for information online. Research has shown that search engine users seem to trust the search engines' ranking uncritically and mostly select top-ranked results. This study further examines search engine users' selection behavior. Drawing from the credibility and information research literature, we test whether the presence or absence of certain credibility cues influences the selection probability of search engine results. In an observational study, participants (N?=?247) completed two information research tasks on preset search engine results pages, on which three credibility cues (source reputation, message neutrality, and social recommendations) as well as the search result ranking were systematically varied. The results of our study confirm the significance of the ranking. Of the three credibility cues, only reputation had an additional effect on selection probabilities. Personal characteristics (prior knowledge about the researched issues, search engine usage patterns, etc.) did not influence the preference for search results linked with certain credibility cues. These findings are discussed in light of situational and contextual characteristics (e.g., involvement, low-cost scenarios).