The Experts below are selected from a list of 242619 Experts worldwide ranked by ideXlab platform
Sudeep Das - One of the best experts on this subject based on the ideXlab platform.
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SIGIR - Challenges in Search on Streaming Services: Netflix Case Study
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019Co-Authors: Sudarshan Lamkhede, Sudeep DasAbstract:We discuss salient challenges of building a Search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the Search Context to aid content discovery and support Searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level Instant Search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.
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Challenges in Search on Streaming Services: Netflix Case Study
arXiv: Information Retrieval, 2019Co-Authors: Sudarshan Lamkhede, Sudeep DasAbstract:We discuss salient challenges of building a Search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the Search Context to aid content discovery and support Searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level instant Search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.
Hiroyuki Kitagawa - One of the best experts on this subject based on the ideXlab platform.
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Conveying taxonomy Context for topic-focused Web Search: ReSearch Articles
Journal of the Association for Information Science and Technology, 2005Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Introducing Context to a user query is effective to improve the Search effectiveness. In this article we propose a method employing the taxonomy-based Search services such as Web directories to facilitate Searches in any Web Search interfaces that support Boolean queries. The proposed method enables one to convey current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the Web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many Web Search interfaces, and to use the condition to modify the user query before forwarding it to the Web Search interfaces. To guarantee that the modified query can always be processed by the Web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed new fast classification learning algorithms. © 2005 Wiley Periodicals, Inc.
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Conveying taxonomy Context for topic‐focused Web Search
Journal of the American Society for Information Science and Technology, 2004Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Introducing Context to a user query is effective to improve the Search effectiveness. In this article we propose a method employing the taxonomy-based Search services such as Web directories to facilitate Searches in any Web Search interfaces that support Boolean queries. The proposed method enables one to convey current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the Web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many Web Search interfaces, and to use the condition to modify the user query before forwarding it to the Web Search interfaces. To guarantee that the modified query can always be processed by the Web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed new fast classification learning algorithms.
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CoopIS/DOA/ODBASE - Taxonomy-Based Context Conveyance for Web Search
On The Move to Meaningful Internet Systems 2003: CoopIS DOA and ODBASE, 2003Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Taxonomy-based Search services such as web directories are good starting points for users to Search information needed from the web. In this paper we propose a method employing the Search services to facilitate Searches in any web Search interfaces that support Boolean queries. The proposed method enables one to convey his current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many web Search interfaces, and use the condition to modify the user query before forwarding it to the web Search interfaces. To guarantee that the modified query can always be processed by the web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed a new fast classification rule learning algorithm. Extensive experiments show that the proposed method can significantly improve the Search result effectiveness of the web Search interfaces.
Jason J. Jung - One of the best experts on this subject based on the ideXlab platform.
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Exploiting semantic annotation to supporting user browsing on the web
Knowledge-Based Systems, 2007Co-Authors: Jason J. JungAbstract:The aim of this paper is to support user browsing on semantically heterogeneous information spaces. In advance of a user's explicit actions, his Search Context should be predicted by the locally annotated resources in his access histories. We thus exploit semantic transcoding method and measure the relevance between the estimated model of user intention and the candidate resources in web spaces. For these experiments, we simulated the scenario of comparison-shopping systems on the testing bed organized by twelve online stores in which images are annotated with semantically heterogeneous metadata.
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KES (3) - Exploring the effective Search Context for the user in an interactive and adaptive way
Lecture Notes in Computer Science, 2005Co-Authors: Supratip Ghose, Jason J. JungAbstract:The explosive growth of information on the web demands effective intelligent Search and filtering methods. Consequently, techniques have been developed that extract conceptual information from the document and use the conceptual information in the user profile to form part of the user's information intent from his/her query. In a similar vein, we build the profile without user interaction, automatically monitoring the user's browsing habits. These profiles, in turn, are used to automatically learn the semantic Context of user's information need. These sets of categories can serve as a Context to disambiguate the words in the user's query. In this paper, we present a framework for assisting the user in one of the most difficult information retrieval tasks, i.e., that of formulating an effective Search query. Our experimental results show that implicit measurements of user interests, combined with the semantic knowledge embedded in a concept hierarchy, can be used effectively to infer the user Context and to improve the results of information retrieval.
Sudarshan Lamkhede - One of the best experts on this subject based on the ideXlab platform.
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SIGIR - Challenges in Search on Streaming Services: Netflix Case Study
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019Co-Authors: Sudarshan Lamkhede, Sudeep DasAbstract:We discuss salient challenges of building a Search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the Search Context to aid content discovery and support Searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level Instant Search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.
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Challenges in Search on Streaming Services: Netflix Case Study
arXiv: Information Retrieval, 2019Co-Authors: Sudarshan Lamkhede, Sudeep DasAbstract:We discuss salient challenges of building a Search experience for a streaming media service such as Netflix. We provide an overview of the role of recommendations within the Search Context to aid content discovery and support Searches for unavailable (out-of-catalog) entities. We also stress the importance of keystroke-level instant Search experience, and the technical challenges associated with implementing it across different devices and languages for a global audience.
Said Mirza Pahlevi - One of the best experts on this subject based on the ideXlab platform.
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Conveying taxonomy Context for topic-focused Web Search: ReSearch Articles
Journal of the Association for Information Science and Technology, 2005Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Introducing Context to a user query is effective to improve the Search effectiveness. In this article we propose a method employing the taxonomy-based Search services such as Web directories to facilitate Searches in any Web Search interfaces that support Boolean queries. The proposed method enables one to convey current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the Web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many Web Search interfaces, and to use the condition to modify the user query before forwarding it to the Web Search interfaces. To guarantee that the modified query can always be processed by the Web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed new fast classification learning algorithms. © 2005 Wiley Periodicals, Inc.
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Conveying taxonomy Context for topic‐focused Web Search
Journal of the American Society for Information Science and Technology, 2004Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Introducing Context to a user query is effective to improve the Search effectiveness. In this article we propose a method employing the taxonomy-based Search services such as Web directories to facilitate Searches in any Web Search interfaces that support Boolean queries. The proposed method enables one to convey current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the Web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many Web Search interfaces, and to use the condition to modify the user query before forwarding it to the Web Search interfaces. To guarantee that the modified query can always be processed by the Web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed new fast classification learning algorithms.
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CoopIS/DOA/ODBASE - Taxonomy-Based Context Conveyance for Web Search
On The Move to Meaningful Internet Systems 2003: CoopIS DOA and ODBASE, 2003Co-Authors: Said Mirza Pahlevi, Hiroyuki KitagawaAbstract:Taxonomy-based Search services such as web directories are good starting points for users to Search information needed from the web. In this paper we propose a method employing the Search services to facilitate Searches in any web Search interfaces that support Boolean queries. The proposed method enables one to convey his current Search Context on taxonomy of a taxonomy-based Search service to the Searches conducted with the web Search interfaces. The basic idea is to learn the Search Context in the form of a Boolean condition that is commonly accepted by many web Search interfaces, and use the condition to modify the user query before forwarding it to the web Search interfaces. To guarantee that the modified query can always be processed by the web Search interfaces and to make the method adaptive to different user requirements on Search result effectiveness, we have developed a new fast classification rule learning algorithm. Extensive experiments show that the proposed method can significantly improve the Search result effectiveness of the web Search interfaces.
