Abstract
The increasing availability of text information coded in many different languages poses new challenges to modern information retrieval and mining systems in order to discover and exchange knowledge at a larger world-wide scale. The 1st International Workshop on Modeling, Learning and Mining for Cross/Multilinguality (dubbed MultiLingMine 2016) provides a venue to discuss research advances in cross-/multilingual related topics, focusing on new multidisciplinary research questions that have not been deeply investigated so far (e.g., in CLEF and related events relevant to CLIR). This includes theoretical and experimental ongoing works about novel representation models, learning algorithms, and knowledge-based methodologies for emerging trends and applications, such as, e.g., cross-view cross-/multilingual information retrieval and document mining, (knowledge-based) translation-independent cross-/ multilingual corpora, applications in social network contexts, and more.
Cite
CITATION STYLE
Ienco, D., Roche, M., Romeo, S., Rosso, P., & Tagarelli, A. (2016). Multilingmine 2016: Modeling, learning and mining for cross/multilinguality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9626, pp. 869–873). Springer Verlag. https://doi.org/10.1007/978-3-319-30671-1_83
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