{"title":"The Information Retrieval Series","description":null,"products":[{"product_id":"information-retrieval-book-david-a-grossman-9781402030048","title":"Information Retrieval","description":"Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions.   This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms.   The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described.    This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.","brand":"WoB","offers":[{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":49562638582033,"sku":"GOR002988921","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50379698012433,"sku":"CIN1402030045VG","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":52105952362769,"sku":"CIN1402030045G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52122683441425,"sku":"NLS9781402030048","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ GOOD \/ INTERNAL","offer_id":53474368225553,"sku":"GOR002988785","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1402030045.jpg?v=1753686461"},{"product_id":"query-understanding-for-search-engines-book-yi-chang-9783030583330","title":"Query Understanding for Search Engines","description":"This book presents a systematic study of practices and theories for query understanding of search engines. These studies can be categorized into three major classes. The first class is to figure out what the searcher wants by extracting semantic meaning from the searcher’s keywords, such as query classification, query tagging, and query intent understanding. The second class is to analyze search queries and then translate them into an enhanced query that can produce better search results, such as query spelling correction or query rewriting. The third class is to assist users in refining or suggesting queries in order to reduce users’ search effort and satisfy their information needs, such as query auto-completion and query suggestion. Query understanding is a fundamental part of search engines. It is responsible to precisely infer the intent of the query formulated by the search user, to correct spelling errors in his\/her query, to reformulate the query to capture its intent more accurately, and to guide the user in formulating a query with precise intent. The book will be invaluable to researchers and graduate students in computer or information science and specializing in information retrieval or web-based systems, as well as to researchers and programmers working on the development or improvement of products related to search engines.","brand":"WoB","offers":[{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50203165065489,"sku":"CIN3030583333VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52333015040273,"sku":"NLS9783030583330","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/3030583333.jpg?v=1751317305"},{"product_id":"social-information-seeking-book-chirag-shah-9783319567556","title":"Social Information Seeking","description":"This volume summarizes the author’s work on social information seeking (SIS), and at the same time serves as an introduction to the topic. Sometimes also referred to as social search or social information retrieval, this is a relatively new area of study concerned with the seeking and acquiring of information from social spaces on the Internet. It involves studying situations, motivations, and methods involved in seeking and sharing of information in participatory online social sites, such as Yahoo! Answers, WikiAnswers, and Twitter, as well as building systems for supporting such activities.  The first part of the book introduces various foundational concepts, including information seeking, social media, and social networking. As such it provides the necessary basis to then discuss how those aspects could intertwine in different ways to create methods, tools, and opportunities for supporting and leveraging SIS. Next, Part II discusses the social dimension and primarily examines the online question-answering activity. Part III then emphasizes the collaborative aspect of information seeking, and examines what happens when social and collaborative dimensions are considered together. Lastly, Part IV provides a synthesis by consolidating methods, systems, and evaluation techniques related to social and collaborative information seeking. The book is completed by a list of challenges and opportunities for both theoretical and practical SIS work.  The book is intended mainly for researchers and graduate students looking for an introduction to this new field, as well as developers and system designers interested in building interactive information retrieval systems or social\/community-driven interfaces.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50404746821905,"sku":"CIN3319567551G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52532626489617,"sku":"NLS9783319567556","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/3319567551.jpg?v=1751189569"},{"product_id":"information-storage-and-retrieval-systems-book-gerald-j-kowalski-9780792379249","title":"Information Storage and Retrieval Systems","description":"Chapter 1 places into perspective a total Information Storage and Retrieval System. This perspective introduces new challenges to the problems that need to be theoretically addressed and commercially implemented. Ten years ago commercial implementation of the algorithms being developed was not realistic, allowing theoreticians to limit their focus to very specific areas. Bounding a problem is still essential in deriving theoretical results. But the commercialization and insertion of this technology into systems like the Internet that are widely being used changes the way problems are bounded. From a theoretical perspective, efficient scalability of algorithms to systems with gigabytes and terabytes of data, operating with minimal user search statement information, and making maximum use of all functional aspects of an information system need to be considered. The dissemination systems using persistent indexes or mail files to modify ranking algorithms and combining the search of structured information fields and free text into a consolidated weighted output are examples of potential new areas of investigation. The best way for the theoretician or the commercial developer to understand the importance of problems to be solved is to place them in the context of a total vision of a complete system. Understanding the differences between Digital Libraries and Information Retrieval Systems will add an additional dimension to the potential future development of systems. 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The basis of a logical  model for IR is the assumption that queries and documents can be  represented effectively by logical formulae. To retrieve a document,  an IR system has to infer the formula representing the query from the  formula representing the document. This logical interpretation of  query and document emphasizes that relevance in IR is an inference  process.    The use of logic to build IR models enables one to obtain models that  are more general than earlier well-known IR models. Indeed, some  logical models are able to represent within a uniform framework  various features of IR systems such as hypermedia links, multimedia  data, and user's knowledge. Logic also provides a common approach to  the integration of IR systems with logical database systems. Finally,  logic makes it possible to reason about an IR model and its  properties. 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Finally,  logic makes it possible to reason about an IR model and its  properties. This latter possibility is becoming increasingly more  important since conventional evaluation methods, although good  indicators of the effectiveness of IR systems, often give results  which cannot be predicted, or for that matter satisfactorily  explained.    However, logic by itself cannot fully model IR. The success or the  failure of the inference of the query formula from the document  formula is not enough to model relevance in IR. It is necessary to  take into account the uncertainty inherent in such an inference  process. In 1986, Van Rijsbergen proposed the uncertainty logical  principle to model relevance as an uncertain inference process. When  proposing the principle, Van Rijsbergen was not specific about which  logic and which uncertainty theory to use. As a consequence, various  logics and uncertainty theories have been proposed and investigated.  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Mining the World Wide Web is designed for researchers and  developers of Web information systems and also serves as an excellent  supplemental reference to advanced level courses in data mining,  databases and information retrieval.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51141448499473,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51141451776273,"sku":"NIN9780792373490","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52406277439761,"sku":"NLS9780792373490","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0792373499.jpg?v=1751044091"},{"product_id":"automatic-indexing-and-abstracting-of-document-texts-book-marie-francine-moens-9780792377931","title":"Automatic Indexing and Abstracting of Document Texts","description":"Automatic Indexing and Abstracting of Document Texts  summarizes the latest techniques of automatic indexing and  abstracting, and the results of their application. 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The second point is significantly different from the Web in general.       The type of search system that we propose in this book can suggest ways of refining or relaxing the query to assist a user in the search process. In order to suggest sensible query modifications we would need to know what the documents are about. Explicit knowledge about the document collection encoded in some electronic form is what we need. However, typically such knowledge is not available. 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Buried on the Internet are both valuable nuggets to answer questions as well as a large quantity of information the average person does not care about. The Digital Library effort is also progressing, with the goal of migrating from the traditional book environment to a digital library environment. The challenge to both authors of new publications that will reside on this information domain and developers of systems to locate information is to provide the information and capabilities to sort out the non-relevant items from those desired by the consumer. In effect, as we proceed down this path, it will be the computer that determines what we see versus the human being. The days of going to a library and browsing the new book shelf are being replaced by electronic searching the Internet or the library catalogs. Whatever the search engines return will constrain our knowledge of what information is available. An understanding of Information Retrieval Systems puts this new environment into perspective for both the creator of documents and the consumer trying to locate information.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52142640300305,"sku":"NLS9781475770322","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781475770322.jpg?v=1757581166"},{"product_id":"advances-in-information-retrieval-book-w-bruce-croft-9781475783605","title":"Advances in Information Retrieval","description":"The Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department ofthe University ofMassachusetts, Amherst in 1992. The core support for the Center came from a National Science Foun- tion State\/Industry\/University Cooperative Research Center(S\/IUCRC) grant, although there had been a sizeable information retrieval (IR) research group for over 10 years prior to that grant. 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This book includes descriptions of the nature of documents,  their components and structure, and how they can be represented;  examines how documents are used and controlled; explores the issues  and factors affecting design and implementation of a document  management strategy; and gives a detailed case study. The analysis and  recommendations are grounded in the findings of the latest research.     Document Computing: Technologies for Managing Electronic  Document Collections brings together concepts, research, and  practice from diverse areas including document computing, information  retrieval, librarianship, records management, and business process  re-engineering. It will be of value to anyone working in these areas,  whether as a researcher, a developer, or a user.    Document Computing: Technologies for Managing Electronic  Document Collections can be used for graduate classes in  document computing and related fields, by developers and integrators  of document management systems and document management applications,  and by anyone wishing to understand the processes of document  management.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52144230334737,"sku":"NLS9781461372509","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781461372509.jpg?v=1757587957"},{"product_id":"advanced-topics-in-information-retrieval-book-massimo-melucci-9783642209451","title":"Advanced Topics in Information Retrieval","description":"Information retrieval is the science concerned with the effective and efficient retrieval of documents starting from their semantic content. It is employed to fulfill some information need from a large number of digital documents. Given the ever-growing amount of documents available and the heterogeneous data structures used for storage, information retrieval has recently faced and tackled novel applications.    In this book, Melucci and Baeza-Yates present a wide-spectrum illustration of recent research results in advanced areas related to information retrieval. Readers will find chapters on e.g. aggregated search, digital advertising, digital libraries, discovery of spam and opinions, information retrieval in context, multimedia resource discovery, quantum mechanics applied to information retrieval, scalability challenges in web search engines, and interactive information retrieval evaluation. All chapters are written by well-known researchers, are completely self-contained and comprehensive, and are complemented by an integrated bibliography and subject index.    With this selection, the editors provide the most up-to-date survey of topics usually not addressed in depth in traditional (text)books on information retrieval. 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One of the goalsof the IR book series is to highlight the work of academic research centers in our ?eld, in order to balancetheperceptionthateveryoneinIRworksforasearchenginecompany. One of the best aspects of our ?eld is that, as academic researchers, we can work with new graduate students and collaborate with companies to ensure that our research has direct impact on systems that people use every day. The Padua group is typical in this respect, and has been involved in a series of collaborations and major European projects over the years. I hope this volume inspires graduate students to pursue research in IR, and I encourage other research groups to contribute their own collections of papers. Amherst, Massachusetts. July 2007. W. Bruce Croft Preface The Information Management Systems (IMS) Research Group was formed in the Department of Information Engineering (formerly Department of El- tronicsandComputer Science)ofthe UniversityofPadua,Italy,in1987when the department was established. The group activities are concerned with the design,modelingandimplementationofadvancedinformationretrievaltools- such as search engines - and digital library systems.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52146186060049,"sku":"NLS9783642094415","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783642094415.jpg?v=1757596864"},{"product_id":"information-retrieval-book-david-a-grossman-9781402030031","title":"Information Retrieval","description":"Interested in how an efficient search engine works? Want to know what algorithms are used to rank resulting documents in response to user requests? The authors answer these and other key information retrieval design and implementation questions.   This book is not yet another high level text. Instead, algorithms are thoroughly described, making this book ideally suited for both computer science students and practitioners who work on search-related applications. As stated in the foreword, this book provides a current, broad, and detailed overview of the field and is the only one that does so. Examples are used throughout to illustrate the algorithms.   The authors explain how a query is ranked against a document collection using either a single or a combination of retrieval strategies, and how an assortment of utilities are integrated into the query processing scheme to improve these rankings. Methods for building and compressing text indexes, querying and retrieving documents in multiple languages, and using parallel or distributed processing to expedite the search are likewise described.    This edition is a major expansion of the one published in 1998. Besides updating the entire book with current techniques, it includes new sections on language models, cross-language information retrieval, peer-to-peer processing, XML search, mediators, and duplicate document detection.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52150570811665,"sku":"NLS9781402030031","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781402030031.jpg?v=1757610527"},{"product_id":"evaluating-information-retrieval-and-access-tasks-book-tetsuya-sakai-9789811555565","title":"Evaluating Information Retrieval and Access Tasks","description":"This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life.    Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants.    This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":52152368333073,"sku":"NGR9789811555565","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52688703521041,"sku":"NLS9789811555565","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9789811555565.jpg?v=1757616416"},{"product_id":"document-computing-book-ross-wilkinson-9780792383574","title":"Document Computing","description":"Document Computing: Technologies for Managing Electronic  Document Collections discusses the important aspects of  document computing and recommends technologies and techniques for  document management, with an emphasis on the processes that are  appropriate when computers are used to create, access, and publish  documents. 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Web mining is a  multidisciplinary field, drawing on such areas as artificial  intelligence, databases, data mining, data warehousing, data  visualization, information retrieval, machine learning, markup  languages, pattern recognition, statistics, and Web technology.  Mining the World Wide Web presents the Web mining material from  an information search perspective, focusing on issues relating to the  efficiency, feasibility, scalability and usability of searching  techniques for Web mining.   Mining the World Wide Web is designed for researchers and  developers of Web information systems and also serves as an excellent  supplemental reference to advanced level courses in data mining,  databases and information retrieval.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ INGRAM","offer_id":52336742400273,"sku":"NLS9781461356547","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":52953461260561,"sku":"NIN9781461356547","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9781461356547.jpg?v=1758164339"},{"product_id":"topic-detection-and-tracking-book-james-allan-9781461353119","title":"Topic Detection and Tracking","description":"The purposeofthis book is to providea recordofthe stateofthe art in Topic Detection and Tracking (TDT) in a single place. Research in TDT has been going on for about five years, and publications related to it are scattered all over the place as technical reports, unpublished manuscripts, or in numerous conference proceedings. The third and fourth in a series of on-going TDT evaluations marked a turning point in the research. As such. it provides an excellent time to pause. review the state of the art. gather lessons learned, and describe the open challenges. This book is a collection oftechnical papers. As such, its primary audience is researchers interested in the the current state of TDT research, researchers who hope to leverage that work sothat theirown efforts can avoid pointlessdu- plication and false starts. It might also pointthem in the direction ofinteresting unsolved problems within the area. The book is also of interest to practition- ers in fields that are related to TDT--e.g., Information Retrieval. Automatic Speech Recognition. Machine Learning, Information Extraction, and so on. 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All major retrieval methods developed so far are described in detail, along with Web retrieval algorithms, and the author shows that they all can be treated elegantly in a unified formal way, using lattice theory as the one basic concept. The book's presentation is characterized by an engineering-like approach.","brand":"WoB","offers":[{"title":"- \/ - \/ INTERNAL","offer_id":52338530746641,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52338534547729,"sku":"NLS9783540776581","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/9783540776581.jpg?v=1758168808"},{"product_id":"feature-centric-view-of-information-retrieval-book-donald-metzler-9783642270178","title":"A Feature-Centric View of Information Retrieval","description":"Commercial Web search engines such as Google, Yahoo, and Bing are used every day by millions of people across the globe. With their ever-growing refinement and usage, it has become increasingly difficult for academic researchers to keep up with the collection sizes and other critical research issues related to Web search, which has created a divide between the information retrieval research being done within academia and industry.  Such large collections pose a new set of challenges for information retrieval researchers.   In this work, Metzler describes highly effective information retrieval models for both smaller, classical data sets, and larger Web collections. In a shift away from heuristic, hand-tuned ranking functions and complex probabilistic models, he presents feature-based retrieval models. The Markov random field model he details goes beyond the traditional yet ill-suited bag of words assumption in two ways. First, the model can easily exploit various types of dependencies that exist between query terms, eliminating the term independence assumption that often accompanies bag of words models. Second, arbitrary textual or non-textual features can be used within the model. As he shows, combining term dependencies and arbitrary features results in a very robust, powerful retrieval model. In addition, he describes several extensions, such as an automatic feature selection algorithm and a query expansion framework. The resulting model and extensions provide a flexible framework for highly effective retrieval across a wide range of tasks and data sets.  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The book describes means by which retrieval may be studied  analytically, allowing one to describe current performance,  predict future performance, and to understand why systems  perform as they do. The focus is on retrieving and filtering natural  language text, with material addressing retrieval performance for the  simple case of queries with a single term, the more complex case with  multiple terms, both with term independence and term dependence, and  for the use of grammatical information to improve performance.  Unambiguous statements of the conditions under which one method or  system will be more effective than another are developed.    Text Retrieval and Filtering: Analytical Models of Performance  focuses on the performance of systems that retrieve natural language  text, considering full sentences as well as phrases and individual  words. The last chapter explicitly addresses how grammatical  constructs and methods may be studied in the context of retrieval or  filtering system performance. The book builds toward solving this  problem, although the material in earlier chapters is as useful to  those addressing non-linguistic, statistical concerns as it is to  linguists. Those interested in grammatical information should be  cautioned to carefully examine earlier chapters, especially Chapters 7  and 8, which discuss purely statistical relationships between terms,  before moving on to Chapter 10, which explicitly addresses linguistic  issues.    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The need for efficient content-based image re- trieval has increased tremendously in many application areas such as biomedicine, the military, commerce, education, and Web image clas- sification and searching. In the biomedical domain, content-based im- age retrieval can be used in patient digital libraries, clinical diagnosis, searching of 2-D electrophoresis gels, and pathology slides. I started my work on content-based image retrieval in 1995 when I was with Stanford University. The project was initiated by the Stan- ford University Libraries and later funded by a research grant from the National Science Foundation. The goal was to design and implement a computer system capable of indexing and retrieving large collections of digitized multimedia data available in the libraries based on the media contents. At the time, it seemed reasonable to me that I should discover the solution to the image retrieval problem during the project. 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The decreasing costs of consumer  electronic devices such as digital cameras and digital camcorders,  along with the ease of transportation facilitated by the Internet, has  lead to a phenomenal rise in the amount of multimedia data generated  and distributed. Given that this trend of increased use of multimedia  data is likely to accelerate, there is an urgent need for providing a  clear means of capturing, storing, indexing, retrieving, analyzing and  summarizing such data.    Content-based access to multimedia data is of primary importance since  it is the natural way by which human beings interact with such  information. To facilitate the content-based access of multimedia  information, the first step is to derive feature measures from these  data so that a feature space representation of the data content can be  formed. This can subsequently allow for mapping the feature space to  the symbol space (semantics) either automatically or through human  intervention. 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