-
Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents
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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/.
- Source
- WWW '02: Proceedings of the 11th International Conference on World Wide Web, May 7-11, 2002, Honolulu, Hawaii, USA
-
Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015)
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- Abstract
- Numerous studies have explored the possibility of uncovering information from web search queries but few have examined the factors that affect web query data sources. We conducted a study that investigated this issue by comparing Google Trends and Baidu Index. Data from these two services are based on queries entered by users into Google and Baidu, two of the largest search engines in the world. We first compared the features and functions of the two services based on documents and extensive testing. We then carried out an empirical study that collected query volume data from the two sources. We found that data from both sources could be used to predict the quality of Chinese universities and companies. Despite the differences between the two services in terms of technology, such as differing methods of language processing, the search volume data from the two were highly correlated and combining the two data sources did not improve the predictive power of the data. However, there was a major difference between the two in terms of data availability. Baidu Index was able to provide more search volume data than Google Trends did. Our analysis showed that the disadvantage of Google Trends in this regard was due to Google's smaller user base in China. The implication of this finding goes beyond China. Google's user bases in many countries are smaller than that in China, so the search volume data related to those countries could result in the same issue as that related to China.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
- Theme
- Data Mining
-
Liu, Y.; Zhang, M.; Cen, R.; Ru, L.; Ma, S.: Data cleansing for Web information retrieval using query independent features (2007)
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- Abstract
- Understanding what kinds of Web pages are the most useful for Web search engine users is a critical task in Web information retrieval (IR). Most previous works used hyperlink analysis algorithms to solve this problem. However, little research has been focused on query-independent Web data cleansing for Web IR. In this paper, we first provide analysis of the differences between retrieval target pages and ordinary ones based on more than 30 million Web pages obtained from both the Text Retrieval Conference (TREC) and a widely used Chinese search engine, SOGOU (www.sogou.com). We further propose a learning-based data cleansing algorithm for reducing Web pages that are unlikely to be useful for user requests. We found that there exists a large proportion of low-quality Web pages in both the English and the Chinese Web page corpus, and retrieval target pages can be identified using query-independent features and cleansing algorithms. The experimental results showed that our algorithm is effective in reducing a large portion of Web pages with a small loss in retrieval target pages. It makes it possible for Web IR tools to meet a large fraction of users' needs with only a small part of pages on the Web. These results may help Web search engines make better use of their limited storage and computation resources to improve search performance.
- Footnote
- Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
- Theme
- Data Mining
-
Drabenstott, K.M.: Web search strategies (2000)
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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
-
Next generation search engines : advanced models for information retrieval (2012)
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- Abstract
- The main goal of this book is to transfer new research results from the fields of advanced computer sciences and information science to the design of new search engines. The readers will have a better idea of the new trends in applied research. The achievement of relevant, organized, sorted, and workable answers- to name but a few - from a search is becoming a daily need for enterprises and organizations, and, to a greater extent, for anyone. It does not consist of getting access to structural information as in standard databases; nor does it consist of searching information strictly by way of a combination of key words. It goes far beyond that. Whatever its modality, the information sought should be identified by the topics it contains, that is to say by its textual, audio, video or graphical contents. This is not a new issue. However, recent technological advances have completely changed the techniques being used. New Web technologies, the emergence of Intranet systems and the abundance of information on the Internet have created the need for efficient search and information access tools.
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.
- Content
- Enthält die Beiträge: Das, A., A. Jain: Indexing the World Wide Web: the journey so far. Ke, W.: Decentralized search and the clustering paradox in large scale information networks. Roux, M.: Metadata for search engines: what can be learned from e-Sciences? Fluhr, C.: Crosslingual access to photo databases. Djioua, B., J.-P. Desclés u. M. Alrahabi: Searching and mining with semantic categories. Ghorbel, H., A. Bahri u. R. Bouaziz: Fuzzy ontologies building platform for Semantic Web: FOB platform. Lassalle, E., E. Lassalle: Semantic models in information retrieval. Berry, M.W., R. Esau u. B. Kiefer: The use of text mining techniques in electronic discovery for legal matters. Sleem-Amer, M., I. Bigorgne u. S. Brizard u.a.: Intelligent semantic search engines for opinion and sentiment mining. Hoeber, O.: Human-centred Web search.
Vert, S.: Extensions of Web browsers useful to knowledge workers. Chen, L.-C.: Next generation search engine for the result clustering technology. Biskri, I., L. Rompré: Using association rules for query reformulation. Habernal, I., M. Konopík u. O. Rohlík: Question answering. Grau, B.: Finding answers to questions, in text collections or Web, in open domain or specialty domains. Berri, J., R. Benlamri: Context-aware mobile search engine. Bouidghaghen, O., L. Tamine: Spatio-temporal based personalization for mobile search. Chaudiron, S., M. Ihadjadene: Studying Web search engines from a user perspective: key concepts and main approaches. Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications. Lewandowski, D.: A framework for evaluating the retrieval effectiveness of search engines.
- LCSH
- Data mining
- Subject
- Data mining
-
Search tools (1997)
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- Abstract
- Offers brief accounts of Internet search tools. Covers the Lycos revamp; the new navigation service produced jointly by Excite and Netscape, delivering a language specific, locally relevant Web guide for Japan, Germany, France, the UK and Australia; InfoWatcher, a combination offline browser, search engine and push product from Carvelle Inc., USA; Alexa by Alexa Internet and WBI from IBM which are free and provide users with information on how others have used the Web sites which they are visiting; and Concept Explorer from Knowledge Discovery Systems, Inc., California which performs data mining from the Web, Usenet groups, MEDLINE and the US Patent and Trademark Office patent abstracts
- Theme
- Data Mining
Web-Agenten
-
Wang, P.; Berry, M.W.; Yang, Y.: Mining longitudinal Web queries : trends and patterns (2003)
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- Abstract
- This project analyzed 541,920 user queries submitted to and executed in an academic Website during a four-year period (May 1997 to May 2001) using a relational database. The purpose of the study is three-fold: (1) to understand Web users' query behavior; (2) to identify problems encountered by these Web users; (3) to develop appropriate techniques for optimization of query analysis and mining. The linguistic analyses focus an query structures, lexicon, and word associations using statistical measures such as Zipf distribution and mutual information. A data model with finest granularity is used for data storage and iterative analyses. Patterns and trends of querying behavior are identified and compared with previous studies.
-
Das, A.; Jain, A.: Indexing the World Wide Web : the journey so far (2012)
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- Abstract
- In this chapter, the authors describe the key indexing components of today's web search engines. As the World Wide Web has grown, the systems and methods for indexing have changed significantly. The authors present the data structures used, the features extracted, the infrastructure needed, and the options available for designing a brand new search engine. Techniques are highlighted that improve relevance of results, discuss trade-offs to best utilize machine resources, and cover distributed processing concepts in this context. In particular, the authors delve into the topics of indexing phrases instead of terms, storage in memory vs. on disk, and data partitioning. Some thoughts on information organization for the newly emerging data-forms conclude the chapter.
-
Baeza-Yates, R.; Hurtado, C.; Mendoza, M.: Improving search engines by query clustering (2007)
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- Abstract
- In this paper, we present a framework for clustering Web search engine queries whose aim is to identify groups of queries used to search for similar information on the Web. The framework is based on a novel term vector model of queries that integrates user selections and the content of selected documents extracted from the logs of a search engine. The query representation obtained allows us to treat query clustering similarly to standard document clustering. We study the application of the clustering framework to two problems: relevance ranking boosting and query recommendation. Finally, we evaluate with experiments the effectiveness of our approach.
- Footnote
- Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
- Theme
- Data Mining
-
Berry, M.W.; Browne, M.: Understanding search engines : mathematical modeling and text retrieval (1999)
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- Abstract
- This book discusses many of the key design issues for building search engines and emphazises the important role that applied mathematics can play in improving information retrieval. The authors discuss not only important data structures, algorithms, and software but also user-centered issues such as interfaces, manual indexing, and document preparation. They also present some of the current problems in information retrieval that many not be familiar to applied mathematicians and computer scientists and some of the driving computational methods (SVD, SDD) for automated conceptual indexing
- LCSH
- Web search engines
- RSWK
- World Wide Web / Suchmaschine / Mathematisches Modell (BVB)
- Subject
- World Wide Web / Suchmaschine / Mathematisches Modell (BVB)
Web search engines
-
Rudich, J.: Internet search engines on CD-ROM (1996)
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- Abstract
- Internet search engines on CD-ROM bridge the gap between printed directories and online search engines. Reviews: CyberSearch, Internet Connection '96, Mega Web directory; New Riders Official World Wide Web Yellow pages, World Wide Web Directory, and WebCompass
- Object
- Mega Web directory
New Riders Official World Wide Web Yellow pages
World Wide Web Directory
-
Li, Z.: ¬A domain specific search engine with explicit document relations (2013)
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- Abstract
- The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.
- Theme
- Semantic Web
-
Shi, X.; Yang, C.C.: Mining related queries from Web search engine query logs using an improved association rule mining model (2007)
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- Abstract
- With the overwhelming volume of information, the task of finding relevant information on a given topic on the Web is becoming increasingly difficult. Web search engines hence become one of the most popular solutions available on the Web. However, it has never been easy for novice users to organize and represent their information needs using simple queries. Users have to keep modifying their input queries until they get expected results. Therefore, it is often desirable for search engines to give suggestions on related queries to users. Besides, by identifying those related queries, search engines can potentially perform optimizations on their systems, such as query expansion and file indexing. In this work we propose a method that suggests a list of related queries given an initial input query. The related queries are based in the query log of previously submitted queries by human users, which can be identified using an enhanced model of association rules. Users can utilize the suggested related queries to tune or redirect the search process. Our method not only discovers the related queries, but also ranks them according to the degree of their relatedness. Unlike many other rival techniques, it also performs reasonably well on less frequent input queries.
- Footnote
- Beitrag eines Themenschwerpunktes "Mining Web resources for enhancing information retrieval"
- Theme
- Data Mining
-
Erlhofer, S.: Suchmaschinen-Optimierung für Webentwickler : Grundlagen, Funktionsweisen und Ranking-Optimierung (2005)
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- RSWK
- World Wide Web / Suchmaschine
Suchmaschine / Web Site / Ranking
- Subject
- World Wide Web / Suchmaschine
Suchmaschine / Web Site / Ranking
-
Fong, W.W.: Searching the World Wide Web (1996)
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- Abstract
- Reviews the availability on the WWW, of search engines designed to organize various web information sources. Discusses the differences and similarities of each search engine and their advantages and disadvantages. Search engines included in the study were: AltaVista, CUI W3 Catalog, InfoSeek, Lycos, Magellan, Yahoo
- Source
- Journal of library and information science. 22(1996) no.1, S.15-36
-
Amato, G.; Rabitti, F.; Savino, P.: Multimedia document search on the Web (1998)
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- Date
- 1. 8.1996 22:08:06
- Footnote
- Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia
-
Lawrence, S.; Giles, C.L.: Searching the World Wide Web (1998)
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-
Lawrence, S.; Giles, C.L.: Searching the World Wide Web (1998)
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Duval, B.K.; Main, L.: Searching the Internet : part 2 trail-blazers (1997)
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- Abstract
- Presents a guide to searching for information on the Internet covering Research-It; familiar quotations: a collection of passages, phrases and proverbs traced to their sources in ancient and modern literature by John Bartlett; the Internet Public Library Reference Center; SearchERIC Database; Britannica Online; Britannica's Lives; The complete works of William Shakespeare; Flicks/Movie Schedules and Reviews; the Electronic Newsstand; CNN Interactive; Time Warner's Pathfinder; Electronic Newspapers from all 50 States; Yahoo, News; Newspapers; Techweb; ZDNet; the On-line Books Page; Columbia University Bartleby Library; the Children's Literature Web Guide; National Institutes of Health; US Census Bureau; Earthquake Info; US Postal Service Zip+4 Lookup; the Federal Web Locator; World Wide Web Virtual Library; US Government Information Sources; Index of the Constitution of the US; US States Code; Find California Code; Dearch for Bills; California Tenant's Rights; The Online Career Center; QuickAID Home Page; City.Net; Netscape's Destinations Button; International Telephone Directory; World Alumni Net; Archives of Adoptees and Birth Parents; and World Wide Registry Matching Adoptees with Birth Parents
- Date
- 6. 3.1997 16:22:15
-
Mukherjea, S.; Hirata, K.; Hara, Y.: Towards a multimedia World-Wide Web information retrieval engine (1997)
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- Abstract
- Describes a search engine that integrate text and image search. 1 or more Web site can be indexed for both textual and image information, allowing the user to search based on keywords or images or both. Another problem with the current search engines is that they show the results as pages of scrolled lists; this is not very user-friendly. The search engine allows the user to visualise to results in various ways. Explains the indexing and searching techniques of the search engine and highlights several features of the querying interface to make the retrieval process more efficient. Use examples to show the usefulness of the technology
- Date
- 1. 8.1996 22:08:06
- Footnote
- Contribution to a special issue of papers from the 6th International World Wide Web conference, held 7-11 Apr 1997, Santa Clara, California
