Temporal features, such as date and time or time of an event, employ concise semantics for any kind of information retrieval, and therefore for linked data information retrieval. However, we have found that most linked data information retrieval techniques pay little attention on the power of temporal feature inclusion. We propose a keyword-based linked data information retrieval framework, called TLDRet, that can incorporate temporal features and give more concise results. Preliminary evaluation of our system shows promising performance. © 2014 Springer International Publishing.
CITATION STYLE
Rahoman, M. M., & Ichise, R. (2014). TLDRet: A temporal semantic facilitated linked data retrieval framework. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8388 LNCS, pp. 228–243). Springer Verlag. https://doi.org/10.1007/978-3-319-06826-8_18
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