Results 11 to 20 of about 624,160 (323)
SPARQL Query Recommendations by Example [PDF]
, 2016 In this demo paper, a SPARQL Query Recommendation Tool (called SQUIRE) based on query reformulation is presented. Based on three steps, Generalization, Specialization and Evaluation, SQUIRE implements the logic of reformulating a SPARQL query that is ...
Adamou, Alessandro +3 more
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Proceedings of the May 19-22, 1975, national computer conference and exposition on - AFIPS '75, 1975 In the last few years we have witnessed a trend to appeal to the non-professional user who has little or virtually no computer or mathematical background.
Moshé M. Zloof
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Proceedings of the June 7-10, 1976, national computer conference and exposition on - AFIPS '76, 1976 Query-by-Example is a high level non-procedural data base language which provides the end user with a simplified unified interface for querying, updating, defining, and maintaining, the data base, as well as imbedding various integrity and authority constraints.
Moshé M. Zloof
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A QUERY BY EXAMPLE MUSIC RETRIEVAL ALGORITHM
Digital Media Processing for Multimedia Interactive Services, 2003 This paper deals with the problem of Query by Example Music Retrieval (QEMR). Retrieving music pieces that are "similar" to a musical query is crucial when exploring very big music databases. The term "similarity" in this paper is equivalent, for instance, to the rules permitting a human subject to build a list of songs to listen to. While the Query by
Hadi Harb, L. CHEN
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A study of query by semantic example [PDF]
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008 In recent years, query-by-semantic-example (QBSE) has become a popular approach to do content based image retrieval. QBSE extends the well established query-by-example retrieval paradigm to the semantic domain. While various authors have pointed out the benefits of QBSE, there are still various open questions with respect to this paradigm.
Nikhil Rasiwasia, Nuno Vasconcelos
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Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018 This paper describes Fuzzy Query By Example, an approach helping users retrieve data without any prior knowledge of the database schema or any formal querying language. The user is solicited to evaluate, in a binary way, pre-selected items of the database.
Aurélien Moreau +2 more
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Query by Example in Remote Sensing Image Archive Using Enhanced Deep Support Vector Data Description
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 This article studies remote sensing image retrieval using kernel-based support vector data description (SVDD). We exploit deep SVDD, which is a well-known method for one-class classification to recover the most relevant samples from the archive.
Omid Ghozatlou +2 more
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Research on data query and application of obstacle dataset based on spatio-temporal data model
Hangkong gongcheng jinzhan, 2023 The obstacle dataset is a kind of aeronautical information dataset based on the aeronautical information exchange model (AIXM) specification proposed by International Civil Aviation Organization (ICAO) under the aviation intelligence management(AIM ...
LAI Xin, LIANG Changsheng, ZHU Meiling
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An Introduction to the Patstat Database with Example Queries [PDF]
Australian Economic Review, 2014 AbstractThis article provides an introduction to the Patstat patent database. It offers guided examples of 10 popular queries that are relevant for research purposes and that cover the most important data tables. It is targeted at academic researchers and practitioners who are willing to learn the basics of the database.
Gaétan de Rassenfosse +2 more
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Query-by-Example On-Device Keyword Spotting [PDF]
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019 A keyword spotting (KWS) system determines the existence of, usually predefined, keyword in a continuous speech stream. This paper presents a query-by-example on-device KWS system which is user-specific. The proposed system consists of two main steps: query enrollment and testing.
Yeonseok Kim +4 more
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