Next Generation Search Engines: Advanced Models for Information Retrieval, Christophe Jouis, Ismail Biskri, Jean-Gabriel Ganascia, Magali Roux
Автор: Buttcher Stefan, Clarke Charles L. A., Cormack Gordon V. Название: Information Retrieval: Implementing and Evaluating Search Engines ISBN: 0262528878 ISBN-13(EAN): 9780262528870 Издательство: MIT Press Рейтинг: Цена: 7618.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An introduction to information retrieval, the foundation for modern search engines, that emphasizes implementation and experimentation.
Information retrieval is the foundation for modern search engines. This textbook offers an introduction to the core topics underlying modern search technologies, including algorithms, data structures, indexing, retrieval, and evaluation. The emphasis is on implementation and experimentation; each chapter includes exercises and suggestions for student projects. Wumpus -- a multiuser open-source information retrieval system developed by one of the authors and available online -- provides model implementations and a basis for student work. The modular structure of the book allows instructors to use it in a variety of graduate-level courses, including courses taught from a database systems perspective, traditional information retrieval courses with a focus on IR theory, and courses covering the basics of Web retrieval. In addition to its classroom use, Information Retrieval will be a valuable reference for professionals in computer science, computer engineering, and software engineering.
Автор: Craven Jenny Название: Systematic Searching ISBN: 1783303735 ISBN-13(EAN): 9781783303731 Издательство: Facet Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In resource poor, cost saving times, this book advises information professionals on how to search more efficiently.
Описание: Diversity in user queries makes it challenging for search engines to effectively return a set of relevant results. Both user intentions to search the web and types of queries are vastly varied; consequently, horizontal and vertical search engines are developed to answer user queries more efficiently. However, these search engines present a variety of problems in web searching.
Result Page Generation for Web Searching: Emerging Research and Opportunities is an essential reference publication that focuses on taking advantages from text and web mining in order to address the issues of recommendation and visualization in web searching. Highlighting a wide range of topics such as navigational searching, resource identification, and ambiguous queries, this book is ideally designed for computer engineers, web designers, programmers, academicians, researchers, and students.
Описание: Algorithms and Applications for Academic Search, Recommendation and Quantitative Association Rule Mining presents novel algorithms for academic search, recommendation and association rule mining that have been developed and optimized for different commercial as well as academic purpose systems. Along with the design and implementation of algorithms, a major part of the work presented in the book involves the development of new systems both for commercial as well as for academic use. In the first part of the book the author introduces a novel hierarchical heuristic scheme for re-ranking academic publications retrieved from standard digital libraries. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. In order to evaluate the performance of the introduced algorithms, a meta-search engine has been designed and developed that submits user queries to standard digital repositories of academic publications and re-ranks the top-n results using the introduced hierarchical heuristic scheme. In the second part of the book the design of novel recommendation algorithms with application in different types of e-commerce systems are described. The newly introduced algorithms are a part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. The initial version of the system uses a novel hybrid recommender (user, item and content based) and provides daily recommendations to all active subscribers of the provider (currently more than 30,000). The recommenders that we are presenting are hybrid by nature, using an ensemble configuration of different content, user as well as item-based recommenders in order to provide more accurate recommendation results.The final part of the book presents the design of a quantitative association rule mining algorithm. Quantitative association rules refer to a special type of association rules of the form that antecedent implies consequent consisting of a set of numerical or quantitative attributes. The introduced mining algorithm processes a specific number of user histories in order to generate a set of association rules with a minimally required support and confidence value. The generated rules show strong relationships that exist between the consequent and the antecedent of each rule, representing different items that have been consumed at specific price levels. This research book will be of appeal to researchers, graduate students, professionals, engineers and computer programmers.
Автор: Noble Safiya Umoja Название: Algorithms of Oppression: How Search Engines Reinforce Racism ISBN: 1479837245 ISBN-13(EAN): 9781479837243 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4138.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As seen in Wired and TimeA revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for "black girls"--what will you find? "Big Booty" and other sexually explicit terms are likely to come up as top search terms. But, if you type in "white girls," the results are radically different. The suggested porn sites and un-moderated discussions about "why black women are so sassy" or "why black women are so angry" presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance--operating as a source for email, a major vehicle for primary and secondary school learning, and beyond--understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century. Safiya Noble discusses search engine bias in an interview with USC Annenberg School for Communication and Journalism
Автор: Noble Safiya Umoja Название: Algorithms of Oppression: How Search Engines Reinforce Racism ISBN: 1479849944 ISBN-13(EAN): 9781479849949 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As seen in Wired and TimeA revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for "black girls"--what will you find? "Big Booty" and other sexually explicit terms are likely to come up as top search terms. But, if you type in "white girls," the results are radically different. The suggested porn sites and un-moderated discussions about "why black women are so sassy" or "why black women are so angry" presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance--operating as a source for email, a major vehicle for primary and secondary school learning, and beyond--understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century. Safiya Noble discusses search engine bias in an interview with USC Annenberg School for Communication and Journalism
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