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The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
Industrial information technologies
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2019, the 26th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC2019) will be held in the south of Europe in Bari, one of the most beautiful and historical cities in Italy. The Bari region’s nickname is “Little California” for its nice weather and Bari's cuisine is one of Italian most traditional , based of local seafood and olive oil. SMC2019 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report up-to-the-minute innovations and developments, summarize stateof-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems and cybernetics. Advances have importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience, and thereby improve quality of life.
2019 IEEE International Professional Communication Conference (ProComm)
The scope of the conference includes the study, development, improvement, and promotion ofeffective techniques for preparing, organizing, processing, editing, collecting, conserving,teaching, and disseminating any form of technical information by and to individuals and groupsby any method of communication. It also includes technical, scientific, industrial, and otheractivities that contribute to the techniques and products used in this field.
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.
Rigorously peer-reviewed forum for publishing early, high-impact results in the areas of uni- and multiprocessors computer systems, computer architecture workload characterization, performance evaluation and simulation techniques, and power-aware computing
Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...
Educational methods, technology, and programs; history of technology; impact of evolving research on education.
Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.
30th Annual International Computer Software and Applications Conference (COMPSAC'06), 2006
As the e-commerce is done faster, there is a continuous flourishing of e-marketplaces. Matchmaking is an important aspect of e-commerce interactions. Recently, an approach has been taken to service matchmaking based on semantic Web technologies; the designed matching rule can be used to find the sellers' compatible advertisements for buyers. In this paper, we define three categories of attributes for ...
Proceedings of the 25th International Conference on Information Technology Interfaces, 2003. ITI 2003., 2003
We propose a new method to create an intelligent Web search agent based on combining rough sets and fuzzy sets. Firstly, we create user profiles which is the important part to approximate query and document. We also design categories of user interests by grouping key terms. We update and create new categories automatically from user feedback. Secondly, we use combined ...
2010 International Conference on Information Retrieval & Knowledge Management (CAMP), 2010
On the one hand, information storage and retrieval through the Internet has made spectacular progress. On the other hand, practical searching for information still confronts us with retrieval systems that are far from perfect. The purpose of this contribution is to clarify the practical state of the art of finding information through image web search systems in a particular subject ...
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2005
The paper addresses a critical problem in deploying a spoken dialog system (SDS). One of the main bottlenecks of SDS deployment for a new domain is data sparseness in building a statistical language model. Our goal is to devise an efficient method to build a reliable language model for a new SDS. We consider the worst, yet quite common, scenario ...
Third International Conference on Information Technology and Applications (ICITA'05), 2005
Within the emergent Semantic Web framework, the use of traditional Web search engines based on keywords provided by the users is not adequate any more. Instead, new methods based on the semantics of user keywords must be defined to search in the vast Web space without incurring in an undesirable loss of information. In this paper we propose a system ...
IEEE Xplore: Search vs. Research
Yesterday, Today and the Next Decade ? James Whittaker, Microsoft
2011 IEEE Awards James H. Mulligan, Jr. Education Medal - Raj Mittra
Learning from Katrina: Search and Rescue Robots for Natural Disasters
New Immersive Mediums - The Search For Egg Yolk: IEEE VICS 2018
Valerie Cross - Similarity from Fuzzy Sets to Semantic Similarity and Their Role on the Semantic Web
LDA to Find User Archetypes for Search & Matching
Dean Kamen's Artificial Arm
An Introduction to Computational Intelligence in Multi-Criteria Decision-Making: The Intersection of Search, Preference Tradeoff
Bari-Bari-II: Jack-Up Rescue Robot with Debris Opening Function
IEEE Top Trends for 2012 at CES: Tipping Point for Video Entertainment on the Web
Dynamic Selection of Evolutionary Algorithm Operators Based on Online Learning and Fitness Landscape Metrics
Surgeons Got Game
Computing Conversations: Rasmus Lerdorf Interview on Creating PHP
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IEEE Xplore: Insider Tips to Improve Your Productivity - Part 1
Some Recent Work in Computational Intelligence for Software Engineering
Why is COLLABORATION better with IEEE Collabratec?
As the e-commerce is done faster, there is a continuous flourishing of e-marketplaces. Matchmaking is an important aspect of e-commerce interactions. Recently, an approach has been taken to service matchmaking based on semantic Web technologies; the designed matching rule can be used to find the sellers' compatible advertisements for buyers. In this paper, we define three categories of attributes for the matchmaking service. Then we present three factors: semantic matching degree, semantic support and relational confidence to capture the semantic characteristics and relationships of the attributes. And we design a semantic ranking MSC combining the three factors to rank the results of advertisements matchmaking. MSC can capture the semantic aspect of matchmaking results; evaluation shows that MSC makes the process of matchmaking more accurately and the advertisement with the highest MSC is better
We propose a new method to create an intelligent Web search agent based on combining rough sets and fuzzy sets. Firstly, we create user profiles which is the important part to approximate query and document. We also design categories of user interests by grouping key terms. We update and create new categories automatically from user feedback. Secondly, we use combined rough and fuzzy sets to refine each query. Each query and document has two parts: a set of core queries and a set of possibly queries. Then we submit a set of queries to WWW search engines. Thirdly, a rough fuzzy set is used to represent each result from WWW search engines. Lastly, we compute a degree of similarity between query and documents for ranking purpose. Using these techniques, we can improve the precision level of the result from WWW search engines that are suitable for individual usage.
On the one hand, information storage and retrieval through the Internet has made spectacular progress. On the other hand, practical searching for information still confronts us with retrieval systems that are far from perfect. The purpose of this contribution is to clarify the practical state of the art of finding information through image web search systems in a particular subject domain and to derive recommendations from the outcome of the investigation. The method of investigation consisted of submitting queries to public access WWW image search engines followed by a quantitative evaluation of the 20 individual results that were ranked highest for each search query; the scoring method leads to a positive score related to precision between 0 and 20 and to a negative score related to misinformation between 0 and minus 20. This has lead to the following findings: Most positive scores were much lower than the ideal maximum, even though the queries contained very specific words and names as formulated by a user familiar with the subject domain. In other words, many image search results lead to information that is irrelevant, so that users lose time and may lose interest. Furthermore and worse, a significant number of search results may even mislead users who are unfamiliar with the selected subject domain. In conclusion, information retrieval from the WWW through image searching is attractive, simple and fast, but precision is far from perfect and users can be misinformed. Recommendations are formulated to authors, publishers, librarians and end-users of image information retrieval systems.
The paper addresses a critical problem in deploying a spoken dialog system (SDS). One of the main bottlenecks of SDS deployment for a new domain is data sparseness in building a statistical language model. Our goal is to devise an efficient method to build a reliable language model for a new SDS. We consider the worst, yet quite common, scenario where only a small amount (/spl sim/1.7 K utterances) of domain specific data is available for the target domain. We present a new method that exploits external static text resources that are collected for other speech recognition tasks as well as dynamic text resources acquired from the World Wide Web (WWW). We show that language models built using external resources can be used jointly with a limited in-domain (baseline) language model to obtain significant improvements in speech recognition accuracy. Combining language models built using external resources with the in-domain language model provides over 20% reduction in WER over the baseline in-domain language model. Equivalently, we achieve almost the same level of performance by having ten times as much in-domain data (17 K utterances).
Within the emergent Semantic Web framework, the use of traditional Web search engines based on keywords provided by the users is not adequate any more. Instead, new methods based on the semantics of user keywords must be defined to search in the vast Web space without incurring in an undesirable loss of information. In this paper we propose a system that takes as input a list of plain keywords provided by the user and outputs equivalent semantic queries expressed in a knowledge representation language, that could be used to retrieve relevant data. For the translation task, specialized agents manage a third-party thesaurus and a pool of pre-existing ontologies to obtain the different meanings of the user keywords and discover semantic relationships between them in run-time.
As you build a Web site, it is worthwhile asking, "Should I put my information where it belongs or where people are most likely to look for it?" Our recent research into improving searching through ontologies is providing some interesting results to answer this question. The techniques developed by our research bring organization to the information received and reconcile the semantics of each document. Our goal is to help users retrieve dynamically generated information that is tailored to their individual needs and preferences. We believe that it is easier for individuals or small groups to develop their own ontologies, regardless of whether global ones are available, and that these can be automatically and ex-post-facto related. We are working to determine the efficacy of local annotation for Web sources, as well as performing reconciliation that is qualified by measures of semantic distance. If successful, this research will enable software agents to resolve the semantic misconceptions that inhibit successful interoperation with other agents and that limit the effectiveness of searching distributed information sources.
To help human users and software agents find relevant knowledge on the Semantic Web, the Swoogle search engine discovers, indexes, and analyzes the ontologies and facts that are encoded in Semantic Web documents.
Along with the fast growth of the World Wide Web, search engine has become one of the most popular services on it. Improvements on the performance of search engines will bring about great economic profit. Aiming at promoting the effectiveness of Web search, a new approach established on the basis of the new concept of section-semantic relation structure is presented. "section" is defined as a block of media that contains a single "atom" of information, and "semantic relation" is defined as the relationship between two sections. New search engines can store the image of the WWW in the section-semantic relation structure, rather than in a keyword index. The storage and processing of section-semantic relation structure is described, and the method of reconstructing the WWW on the basis of this structure is presented. Finally, the advantages of the current approach to the existing search engines is discussed by using a sample.
Personalized Web Search becomes nowadays a promising option in the field of Information Retrieval and search engines design by improving both output quality and user experience. In this paper, we present and evaluate the subsystem, which conducts the Advanced and Personalized search of PeRSSonal, a web-based mechanism for the retrieval, processing and presentation of articles and RSS feeds collected from major news portals of the Internet. The proposed technique uses information explicitly provided by the user in his profile as well as information that the mechanism can learn from the userpsilas behavior during his search and browsing sessions in the system. As this behavior dynamically evolves, the same happens to the userpsilas interests under the prism of the search engine. By adopting this user-centric approach, we manage to present the user with better-refined and more focused results, incorporating his personal preferences to the output. The algorithm operates not in a stand-alone manner but it co-operates and binds with the rest of modules of PeRSSonal in order to accomplish maximum integration with the system. Furthermore, we introduce an enhancement in the search function, based on cached results from past search sessions of each user individually.
The massive distributed, dynamical and evolutionary characteristics of World Wide Web inspire us study it drawing on the Information Foraging Theory which assumes that people prefer yield more useful information per unit cost. Understanding the value of implicit measures is also important to help World Wide Web users search more effectively. Borrowing idea from information foraging theory we propose a method to estimate the Web page information gain based on the implicit measures analysis. We developed an experimental search platform to record the URLs of the pages be browsed, the time spent reading, the time spent scrolling and the number of links be clicked. We analyzed these data using multiple linear regression modeling and obtained a regression function which could be used in calculating the information profitability of the Web pages. Then we regrouped the Web pages searched out by the descending order of the Web page information profitability. We also reported experimental data to show that the search results be regrouped can increase searching efficiency. The findings suggest that the combination of information foraging theory and implicit measures analysis support effective Web-search interaction for everyone.
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