Conference Paper

Query Modification Based on Real-World Contexts for Mobile and Ubiquitous Computing Environments

Kyoto University, Japan
DOI: 10.1109/MDM.2006.132 Conference: Mobile Data Management, 2006. MDM 2006. 7th International Conference on
Source: IEEE Xplore


With the growing amount of information on the WWW and the improvement of mobile computing environments, mobile Web search engines will increase significance or more in the future. Because mobile devices have the restriction of output performance and we have little time for browsing information slowly while moving or doing some activities in the real world, it is necessary to refine the retrieval results in mobile computing environments better than in fixed ones. However, since a mobile user’s query is often shorter and more ambiguous than a fixed user’s query which is not enough to guess his/her information demand accurately, too many results might be retrieved by commonly used Web search engines. This paper proposes two novel methods for query modification based on real-world contexts of a mobile user, such as his/her geographic location and the objects surrounding him/her, aiming to enhance location-awareness, and moreover, context-awareness, to the existing location-free information retrieval systems.

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Available from: Katsumi Tanaka, Feb 24, 2014
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    • "For Evaluation, the authors did some experimentation which indicated that the approximate precision of the results retrieved by adding a name of place or object is improved to some extent, compared with one by adding none to the original query [15]. But on the other hand, they indicated that the relevance measure needs to be improved due to inaccurate results and that will be done in their future work. "
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    ABSTRACT: Web access, especially through search, is by far one of the most popular operations performed on mobile devices. It is very interesting how the Mobile and Social worlds have significantly converged in many interesting ways, the least of which is the ability to simply access social networks on the move. However, much literature indicates how search results, and in specific mobile search is far from satisfactory in terms of meeting user intent and need. This has ultimately led to the introduction of context-aware web search to obtain more adequate results. In this research, we focus on using social context obtained from user social networks to refine search queries. Our initial target is to propose a system that will ultimately demonstrate the effectiveness of integrating this type of context when conducting mobile search. We also describe how we will utilize this system to classify user queries issued on mobile devices to determine the degree by which social context used, to then reformulate the queries by augmenting relevant context, and then finally ranking the results to match user needs.
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    • "There are some proposals which include an ontological user profile [3] and presented a context model to determine user's interests [4] or re-rank search results according to the profile created while user is searching the web [5] [6], but basically they consider desktop users only. Some earlier proposals used ontologies to represent user profile [7], others include some context [8] elements but usually limited to the geographic location. Some approaches used clustering of the web results [9]. "

    Full-text · Conference Paper · Jan 2012
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    • "There are enough researches about a word prediction method which utilizes context of a user. Hattori et al.[6] have proposed a method of query modification and guessing of search keywords based on Real-World contexts, such as user's geographic location or the real objects surrounding the user. Also, the assistant system for writing a document on the web has been proposed[7]. "
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    ABSTRACT: In this paper, we propose a context-aware Input Method Editor (IME) as a ubiquitous service for improving the input of text on mobile devices. In our proposed IME, it estimates the context of users according to position information from GPS (Global Positioning System) sensor or a presence information from the Internet. Simultaneously, it generates a personal context-aware dictionary dynamically from the keywords gotten via some APIs in the Internet. Currently, the information of user’s context is also provided by NGN. In this paper, we explain the overview of our proposal and prototype implementation in Japanese.
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