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A proposal of a temporal semantics aware linked data information retrieval framework

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Abstract

Temporal features, such as an explicit date and time or a time-specific event, employ concise semantics for any kind of information retrieval. Therefore, temporal features should be suitable for linked data information retrieval. However, we have found that most linked data information retrieval techniques pay little attention to the power of temporal feature inclusion. We propose a keyword-based linked data information retrieval framework ‘ that can incorporate temporal features and give more concise results. The evaluation of our system performance indicates that it is promising.

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Notes

  1. Linked data, as of September 2011, used to hold 295 datasets consisting of over 31 billion RDFs, which got increased to 1000 datasets by April 2014.

  2. http://www.w3.org/TR/owl-time/.

  3. http://motools.sourceforge.net/timeline/timeline.html.

  4. http://www.timexportal.info/.

  5. http://timeml.org/site/publications/specs.html.

  6. TLDRet+ is an extension of the previous framework called TLDRet (Rahoman & Ichise 2013).

  7. http://www.timeml.org/site/tarsqi/toolkit/.

  8. Date of execution 5th March 2016.

  9. http://www.timeml.org/tempeval2/tempeval2-trial/guidelines/timex3guidelines-072009.pdf.

  10. http://greententacle.techfak.uni-bielefeld.de/~cunger/qald/2/dbpedia-test-questions.xml.

  11. The questions are DBpedia QALD-1 training Q.# 8 and test Q.# 11, 24, 41; DBpedia QALD-2 training Q.# 2, 37, 39, 52, 90, 91 and test Q.#7, 12, 25, 56, 71, 74, 92, 94; MusicBrainz QALD-1 training Q.# 3, 6, 10, 12, 13, 14, 21, 23, 26, 28, 30, 31, 41, 49, 66, 72, 77, 89, 100 and test Q.# 1, 3, 7; MusicBrainz QALD-2 training Q.# 3, 10, 12, 13, 14, 21, 23, 26, 28, 31, 67, 72, 77, 89, 99, 100 and test Q.# 1, 3, 7, 16.

  12. http://greententacle.techfak.uni-bielefeld.de/~cunger/qald/2/\dbpedia-test-questions.xml.

  13. It includes language model loading time as well.

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Authors and Affiliations

  1. Department of Informatics, SOKENDAI, Tokyo, Japan

    Md-Mizanur Rahoman & Ryutaro Ichise

  2. Department of Computer Science & Engineering, Begum Rokeya University, Rangpur, Bangladesh

    Md-Mizanur Rahoman

  3. National Institute of Informatics, Tokyo, Japan

    Ryutaro Ichise

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  1. Md-Mizanur Rahoman
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  2. Ryutaro Ichise
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Correspondence to Md-Mizanur Rahoman.

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Rahoman, MM., Ichise, R. A proposal of a temporal semantics aware linked data information retrieval framework. J Intell Inf Syst 50, 573–595 (2018). https://doi.org/10.1007/s10844-017-0483-2

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