Conferences related to Web search

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2011 IEEE Asia-Pacific Services Computing Conference (APSCC)

The services computing is a new cross-discipline that covers the science and technology needed to bridge the gap between business services and IT/telecommunication services.

  • 2010 Asia-Pacific Services Computing Conference (APSCC)

    IT/telecommunication-driven business services and application services, as well as to identify emerging research topics and define the future irections of Services Computing.

  • 2009 IEEE Asia-Pacific Services Computing Conference (APSCC)

    IEEE APSCC 2009 is an important forum for researchers and industry practitioners to exchange information regarding advancements in the state of art and practice of IT/telecommunication-driven business services and application services, as well as to identify emerging research topics and define the future directions of Services Computing

  • 2008 IEEE Asia-Pacific Services Computing Conference (APSCC)

    Services Computing is a new cross-discipline that covers the science and technology needed to bridge the gap between business services and IT services. The goal of services computing is to develop new computing technology and thereby enable more advanced IT services to support business services more efficiently and effectively. IEEE APSCC 2008 is an important forum for researchers and industry practitioners to exchange information regarding advancements in the state of art and practice


2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

Web Technologies, Semantic Web, Social Networks and Ubiquitous Intelligence, Knowledge Grids and Grid Intelligence, Web Agents, Web Services, Intelligent Human Web Interaction, Web Support systems, Autonomous oriented computing, Agent and Multi-agent Systems Modeling, Agent and Multi-agent Systems engineering, Coordination, Autonomous auctions and negotiation, Autonomous knowledge and information agents, distributed problem solving, and Applications.

  • 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT)

    Web Intelligence (WI) has been recognized as a new direction for scientific research and development to explore the fundamental roles as well as practical impacts of Artificial Intelligence (AI) [E.g., knowledge representation, planning, knowledge discovery and data mining, intelligent agents, and social network intelligence) and advanced Information Technology (IT) [E.g., wireless networks, ubiquitous devices, social networks, semantic Web, wisdom Web, and data/knowledge grids) on the next generation of We


2010 4th International Conference on Intelligent Information Technology Application (IITA)

IITA 2010 provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspects of intelligent information technology

  • 2009 Third International Symposium on Intelligent Information Technology Application (IITA)

    IITA 2009 provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in any aspects of intelligent information technology. This year, we especially encourage papers on machine learning, signal Processing, communication Systems, circuits and Systems etc. We also welcome papers that highlight successful modern applications of Intelligent Information Technology, such as Multimedia ,Bioinformatics, Power, Neural Systems, Control and so on

  • 2008 Second International Symposium on Intelligent Information Technology Application (IITA)

    T-1 Neural networks and Applications T-2 Machine Learning T-3 Multimedia System and Applications T-4 Speech Processing T-5 Image & video Signal Processing T-6 Computer Aided Network Design T-7 Intelligent Robot T-8 Intelligent Circuits and Systems T-9 Industry Application T-10 Other Related Intelligent Infotmation Applications


2010 IEEE 2nd International Advance Computing Conference (IACC 2010)

Organizations and Institutions are competing to take leads in different areas of advance computing. Due to increasing complexity and size of problems the importance of this area has grown tremendously. The problems which were out of bounds to the computer scientists are now being solved using advance computing technologies. It has opened the flood gates for new research and innovations. In this endeavor we have taken an initiative to provide a common platform for all who are involved in this field.

  • 2009 IEEE International Advance Computing Conference (IACC 2009)

    In Computer Science the problem complexity and size is increasing. The Projects are becomingincreasingly difficult and huge in volume. Therefore the area of advance computing techniques in terms of efficient algorithms and reliable computing technologies is becoming of utmostimportance. This conference will work towards bridging the gap regarding the solution of the latest problems and the available techniques and technologies.


2009 Third International Conference on Advances in Semantic Processing (SEMAPRO)

With the progress on ontology, web services, semantic social media, semantic web, deep web search /deep semantic web/, semantic deep web, semantic networking and semantic reasoning, SEMAPRO 2009 constitutes the stage for the state-of-the-art on the most recent advances.


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Periodicals related to Web search

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Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Parallel and Distributed Systems, IEEE Transactions on

IEEE Transactions on Parallel and Distributed Systems (TPDS) is published monthly. Topic areas include, but are not limited to the following: a) architectures: design, analysis, and implementation of multiple-processor systems (including multi-processors, multicomputers, and networks); impact of VLSI on system design; interprocessor communications; b) software: parallel languages and compilers; scheduling and task partitioning; databases, operating systems, and programming environments for ...



Most published Xplore authors for Web search

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Xplore Articles related to Web search

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Discovering Web Services in Search Engines

Eyhab Al-Masri; Qusay H. Mahmoud IEEE Internet Computing, 2008

Web service access points are no longer a scarce resource, and the process of discovering them is no longer attached to service registries as Web search engines have become a new major source for Web services. Unfortunately, these separate but distinct approaches to service discovery make it unclear whether provisional registry specifications and search-engine technologies will eventually emerge or coexist.


Dimension Reduction for Supervised Ordering

Toshihiro Kamishima; Shotaro Akaho Sixth International Conference on Data Mining (ICDM'06), 2006

Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal data are being developed, particularly methods for a supervised ordering task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two dimension reduction methods specifically designed to improve prediction ...


Development of a New Corpus System for English Writing Support and its Fundamental Study

M. Murakami; M. Kimura; N. Honda 2006 IEEE International Conference on Fuzzy Systems, 2006

First Page of the Article ![](/xploreAssets/images/absImages/01681990.png)


Improved Semantic Retrieval Based on Domain Ontology

Dong-hui Yuan; Da-you Liu; Shi-qun Shen; Pu Yan 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009

Semantic retrieval is a hot area of Web search technology constantly because of the growing information. This paper proposed a creative semantic retrieval method with Path Weight Semantic Distance (PWSD) algorithm which is improved from current model. Based on the domain ontology built by protege, PWSD considers both the hierarchy and the property restrictions of the concepts synthetically, and provides ...


Webpage importance analysis using conditional Markov random walk

Tie-Yan Liu; Wei-Ying Ma The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05), 2005

In this paper, we propose a novel method to calculate the Web page importance based on a conditional Markov random walk model. The main assumption in this model is that given the hyperlinks in a Web page, users are not really randomly clicking one of them. Instead, many factors may bias their behaviors, for example, the anchor text, the content ...


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Educational Resources on Web search

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eLearning

Discovering Web Services in Search Engines

Eyhab Al-Masri; Qusay H. Mahmoud IEEE Internet Computing, 2008

Web service access points are no longer a scarce resource, and the process of discovering them is no longer attached to service registries as Web search engines have become a new major source for Web services. Unfortunately, these separate but distinct approaches to service discovery make it unclear whether provisional registry specifications and search-engine technologies will eventually emerge or coexist.


Dimension Reduction for Supervised Ordering

Toshihiro Kamishima; Shotaro Akaho Sixth International Conference on Data Mining (ICDM'06), 2006

Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal data are being developed, particularly methods for a supervised ordering task: i.e., learning functions used to sort objects from sample orders. In this article, we propose two dimension reduction methods specifically designed to improve prediction ...


Development of a New Corpus System for English Writing Support and its Fundamental Study

M. Murakami; M. Kimura; N. Honda 2006 IEEE International Conference on Fuzzy Systems, 2006

First Page of the Article ![](/xploreAssets/images/absImages/01681990.png)


Improved Semantic Retrieval Based on Domain Ontology

Dong-hui Yuan; Da-you Liu; Shi-qun Shen; Pu Yan 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009

Semantic retrieval is a hot area of Web search technology constantly because of the growing information. This paper proposed a creative semantic retrieval method with Path Weight Semantic Distance (PWSD) algorithm which is improved from current model. Based on the domain ontology built by protege, PWSD considers both the hierarchy and the property restrictions of the concepts synthetically, and provides ...


Webpage importance analysis using conditional Markov random walk

Tie-Yan Liu; Wei-Ying Ma The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05), 2005

In this paper, we propose a novel method to calculate the Web page importance based on a conditional Markov random walk model. The main assumption in this model is that given the hyperlinks in a Web page, users are not really randomly clicking one of them. Instead, many factors may bias their behaviors, for example, the anchor text, the content ...


More eLearning Resources

IEEE-USA E-Books

  • No title

    Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. R nking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, col aborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Learning to Rank / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work

  • No title

    In this book, we aim to provide a fairly comprehensive overview of the scalability and efficiency challenges in large-scale web search engines. More specifically, we cover the issues involved in the design of three separate systems that are commonly available in every web-scale search engine: web crawling, indexing, and query processing systems. We present the performance challenges encountered in these systems and review a wide range of design alternatives employed as solution to these challenges, specifically focusing on algorithmic and architectural optimizations. We discuss the available optimizations at different computational granularities, ranging from a single computer node to a collection of data centers. We provide some hints to both the practitioners and theoreticians involved in the field about the way large- scale web search engines operate and the adopted design choices. Moreover, we survey the efficiency literature, providing pointers to a large number of relatively impo tant research papers. Finally, we discuss some open research problems in the context of search engine efficiency.

  • No title

    With the rapid growth of web search in recent years the problem of modeling its users has started to attract more and more attention of the information retrieval community. This has several motivations. By building a model of user behavior we are essentially developing a better understanding of a user, which ultimately helps us to deliver a better search experience. A model of user behavior can also be used as a predictive device for non-observed items such as document relevance, which makes it useful for improving search result ranking. Finally, in many situations experimenting with real users is just infeasible and hence user simulations based on accurate models play an essential role in understanding the implications of algorithmic changes to search engine results or presentation changes to the search engine result page. In this survey we summarize advances in modeling user click behavior on a web search engine result page. We present simple click models as well as more complex mod ls aimed at capturing non-trivial user behavior patterns on modern search engine result pages. We discuss how these models compare to each other, what challenges they have, and what ways there are to address these challenges. We also study the problem of evaluating click models and discuss the main applications of click models.

  • No title

    The time-worn aphorism "close only counts in horseshoes and hand grenades" is clearly inadequate. Close also counts in golf, shuffleboard, archery, darts, curling, and other games of accuracy in which hitting the precise center of the target isn't to be expected every time, or in which we can expect to be driven from the target by skilled opponents. This book is not devoted to sports discussions, but to efficient algorithms for determining pairs of closely related web pages--and a few other situations in which we have found that inexact matching is good enough -- where proximity suffices. We will not, however, attempt to be comprehensive in the investigation of probabilistic algorithms, approximation algorithms, or even techniques for organizing the discovery of nearest neighbors. We are more concerned with finding nearby neighbors; if they are not particularly close by, we are not particularly interested. In thinking of when approximation is sufficient, remember the of -told joke about two campers sitting around after dinner. They hear noises coming towards them. One of them reaches for a pair of running shoes, and starts to don them. The second then notes that even with running shoes, they cannot hope to outrun a bear, to which the first notes that most likely the bear will be satiated after catching the slower of them. We seek problems in which we don't need to be faster than the bear, just faster than the others fleeing the bear.

  • No title

    As information becomes more ubiquitous and the demands that searchers have on search systems grow, there is a need to support search behaviors beyond simple lookup. Information seeking is the process or activity of attempting to obtain information in both human and technological contexts. Exploratory search describes an information-seeking problem context that is open-ended, persistent, and multifaceted, and information-seeking processes that are opportunistic, iterative, and multitactical. Exploratory searchers aim to solve complex problems and develop enhanced mental capacities. Exploratory search systems support this through symbiotic human-machine relationships that provide guidance in exploring unfamiliar information landscapes. Exploratory search has gained prominence in recent years. There is an increased interest from the information retrieval, information science, and human-computer interaction communities in moving beyond the traditional turn-taking interaction model support d by major Web search engines, and toward support for human intelligence amplification and information use. In this lecture, we introduce exploratory search, relate it to relevant extant research, outline the features of exploratory search systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratory search. Exploratory search is a new frontier in the search domain and is becoming increasingly important in shaping our future world. Table of Contents: Introduction / Defining Exploratory Search / Related Work / Features of Exploratory Search Systems / Evaluation of Exploratory Search Systems / Future Directions and concluding Remarks

  • No title

    Today, Web search is treated as a solitary experience. Web browsers and search engines are typically designed to support a single user, working alone. However, collaboration on information-seeking tasks is actually commonplace. Students work together to complete homework assignments, friends seek information about joint entertainment opportunities, family members jointly plan vacation travel, and colleagues jointly conduct research for their projects. As improved networking technologies and the rise of social media simplify the process of remote collaboration, and large, novel display form- factors simplify the process of co-located group work, researchers have begun to explore ways to facilitate collaboration on search tasks. This lecture investigates the who, what, where, when and why of collaborative search, and gives insight in how emerging solutions can address collaborators' needs. Table of Contents: Introduction / Who? / What? / Where? / When? / Why? / Conclusion: How?

  • No title

    Datacenter networks provide the communication substrate for large parallel computer systems that form the ecosystem for high performance computing (HPC) systems and modern Internet applications. The design of new datacenter networks is motivated by an array of applications ranging from communication intensive climatology, complex material simulations and molecular dynamics to such Internet applications as Web search, language translation, collaborative Internet applications, streaming video and voice-over-IP. For both Supercomputing and Cloud Computing the network enables distributed applications to communicate and interoperate in an orchestrated and efficient way. This book describes the design and engineering tradeoffs of datacenter networks. It describes interconnection networks from topology and network architecture to routing algorithms, and presents opportunities for taking advantage of the emerging technology trends that are influencing router microarchitecture. With the emerge ce of "many-core" processor chips, it is evident that we will also need "many-port" routing chips to provide a bandwidth-rich network to avoid the performance limiting effects of Amdahl's Law. We provide an overview of conventional topologies and their routing algorithms and show how technology, signaling rates and cost-effective optics are motivating new network topologies that scale up to millions of hosts. The book also provides detailed case studies of two high performance parallel computer systems and their networks. Table of Contents: Introduction / Background / Topology Basics / High-Radix Topologies / Routing / Scalable Switch Microarchitecture / System Packaging / Case Studies / Closing Remarks

  • Distributed Information Discovery

    This chapter contains sections titled: Web Search Programs, Federated Digital Libraries, Research on Alternative Approaches to Distributed Searching, Beyond Searching

  • No title

    In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine- readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descriptions that refer to the same entity appearing either within or across knowledge bases. The objective of this book is to present the new entity resolution challenges stemming from the openness of the Web of data in describing entities by an unbounded number of knowledge bases, the semantic and structural diversity of the descriptions provided across domains even for the same real-world entities, a well as the autonomy of knowledge bases in terms of adopted processes for creating and curating entity descriptions. The scale, diversity, and graph structuring of entity descriptions in the Web of data essentially challenge how two descriptions can be effectively compared for similarity, but also how resolution algorithms can efficiently avoid examining pairwise all descriptions. The book covers a wide spectrum of entity resolution issues at the Web scale, including basic concepts and data structures, main resolution tasks and workflows, as well as state-of-the-art algorithmic techniques and experimental trade-offs.

  • No title

    The time-worn aphorism "close only counts in horseshoes and hand-grenades" is clearly inadequate. Close also counts in golf, shuffleboard, archery, darts, curling, and other games of accuracy in which hitting the precise center of the target isn't to be expected every time, or in which we can expect to be driven from the target by skilled opponents. This lecture is not devoted to sports discussions, but to efficient algorithms for determining pairs of closely related web pages -- and a few other situations in which we have found that inexact matching is good enough; where proximity suffices. We will not, however, attempt to be comprehensive in the investigation of probabilistic algorithms, approximation algorithms, or even techniques for organizing the discovery of nearest neighbors. We are more concerned with finding nearby neighbors; if they are not particularly close by, we are not particularly interested. In thinking of when approximation is sufficient, remember the oft- told joke about two campers sitting around after dinner. They hear noises coming towards them. One of them reaches for a pair of running shoes, and starts to don them. The second then notes that even with running shoes, they cannot hope to outrun a bear, to which the first notes that most likely the bear will be satiated after catching the slower of them. We seek problems in which we don't need to be faster than the bear, just faster than the others fleeing the bear.



Standards related to Web search

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Jobs related to Web search

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