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Wearable queries: adapting common retrieval needs to data and users

Published: 30 August 2013 Publication History

Abstract

The wealth of information generated by users interacting with the network and its applications is often under-utilized due to complications in accessing heterogeneous and dynamic data and in retrieving relevant information from sources having possibly unknown formats and structures. Processing complex requests on such information sources is, thus, costly, though not guaranteeing user satisfaction. Furthermore, dynamic contexts prevent substantial user involvement in the interpretation of requests.
The paper envisions an innovative solution to process the above mentioned requests, limiting user involvement by exploiting information on: (a) user context (geo-location, interests, needs); (b) data and processing quality; (c) similar requests repeated over time. By interpreting a request in a novel way by means of a Wearable Query (WQ), i.e., a query that captures the user and request specificities, we envision an approach to address repeated information needs in distributed, heterogeneous, dynamic environments, with emphasis on the geo-spatial dimension and on data quality.

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Cited By

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  • (2020)A User-Aware and Semantic Approach for Enterprise SearchNatural Language Processing10.4018/978-1-7998-0951-7.ch016(302-321)Online publication date: 2020
  • (2019)Exploiting context and quality for linked data source selectionProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3297503(2251-2258)Online publication date: 8-Apr-2019
  • (2018)A User-Aware and Semantic Approach for Enterprise SearchInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201810010714:4(129-146)Online publication date: 1-Oct-2018
  • Show More Cited By

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      cover image ACM Other conferences
      DBRank '13: Proceedings of the 7th International Workshop on Ranking in Databases
      August 2013
      36 pages
      ISBN:9781450324977
      DOI:10.1145/2524828
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      New York, NY, United States

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      Published: 30 August 2013

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      View all
      • (2020)A User-Aware and Semantic Approach for Enterprise SearchNatural Language Processing10.4018/978-1-7998-0951-7.ch016(302-321)Online publication date: 2020
      • (2019)Exploiting context and quality for linked data source selectionProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3297503(2251-2258)Online publication date: 8-Apr-2019
      • (2018)A User-Aware and Semantic Approach for Enterprise SearchInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201810010714:4(129-146)Online publication date: 1-Oct-2018
      • (2016)Crowdsourcing strategies for smart cities applicationsProceedings of the XII Brazilian Symposium on Information Systems on Brazilian Symposium on Information Systems: Information Systems in the Cloud Computing Era - Volume 110.5555/3021955.3022041(510-517)Online publication date: 17-May-2016
      • (2015)Adaptively Approximate Techniques in Distributed ArchitecturesSOFSEM 2015: Theory and Practice of Computer Science10.1007/978-3-662-46078-8_7(65-77)Online publication date: 2015

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