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N. Rekabsaz, R. Bierig, M. Lupu, A. Hanbury:
"Toward Optimized Multimodal Concept Indexing";
Vortrag: International KEYSTONE Conference (IKC), Coimbra Portugal; 08.09.2015 - 09.09.2015; in: "Semantic Keyword-based Search on Structured Data Sources", Springer, 9398 (2015), ISBN: 978-3-319-27932-9; S. 141 - 152.

Information retrieval on the (social) web moves from a pure term-frequency-based approach to an enhanced method that includes conceptual multimodal features on a semantic level. In this paper, we present an approach for semantic-based keyword search and focus especially on its optimization to scale it to real-world sized collections in the social media domain. Furthermore, we present a faceted indexing framework and architecture that relates content to semantic concepts to be indexed and searched semantically. We study the use of textual concepts in a social media domain and observe a significant improvement from using a concept-based solution for keyword searching. We address the problem of time-complexity that is critical issue for concept-based methods by focusing on optimization to enable larger and more real-world style applications.

Semantic Indexing, Concept, Social Web, Word2Vec

http://dx.doi.org/10.1007/978-3-319-27932-9