About LiMoSINe

Posted by Anne Schuth

We increasingly live our life online. Information is accumulated on a wide range of human activities, from science and facts, to personal content, opinions, and trends. Across the globe, people’s knowledge, experiences and interactions effortlessly find their way to online outlets, alongside traditional edited content, ready to be shared with millions. LiMoSINe will integrate the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology. See about for more information.

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News

Infographic for Streamwatchr.com

Posted by Manos Tsagkias

Wondering what Streamwatchr.com is about? Check out our latest infographic!

LiMoSINE Infographic

Posted by Manos Tsagkias

We have released a new infographic for LiMoSINe. Check it out!

Press dossier for LiMoSINe

Posted by Manos Tsagkias

LiMoSINe has now an updated press dossier. It describes in simple language what the project is about and the project's achievements so far. 

Learning Similarity Functions for Topic Detection in Online Reputation Monitoring

Spina, D., Gonzalo J., & Amigó E. (2014).  Learning Similarity Functions for Topic Detection in Online Reputation Monitoring. SIGIR '14: 37th international ACM SIGIR conference on Research and development in information retrieval.

Towards the algebraization of Formal Concept Analysis over complete dioids

Valverde-Albacete, F.  J., & Peláez-Moreno C. (2014).  Towards the algebraization of Formal Concept Analysis over complete dioids. Actas del XVII Congreso Español sobre Tecnolog{\'ıas y Lógica Fuzzy, ESTYLF 2014. 93–98.

User Behavior and Bias in Click-Based Recommender Evaluation

Hofmann, K., Schuth A., Bellogin A., & de Rijke M. (2014).  User Behavior and Bias in Click-Based Recommender Evaluation. 36th European Conference on Information Retrieval (ECIR’14).

Optimizing Base Rankers Using Clicks: A Case Study using BM25

Schuth, A., Sietsma F., Whiteson S., & de Rijke M. (2014).  Optimizing Base Rankers Using Clicks: A Case Study using BM25. 36th European Conference on Information Retrieval (ECIR’14).