This paper describes the experiments carried out as part of the participation in FIRE-2014 Transliterated Search Shared task. We participated in subtask-2 and submitted two results generated by systems based on relevant feedback approach. Given a collection of documents in mixed script, the task is to retrieve relevant documents using queries in either script. The spelling variation between dif...

Many evaluation measures in Information Retrieval (IR) can be viewed as simple user models. Meanwhile, search logs provide us with information about how real users search. This paper describes our attempts to reconcile click log information with user-centric IR measures, bringing the measures into agreement with the logs. Studying the discount curve of NDCG and RBP leads us to extend them, inco...

We extend performance measures commonly used in semantic web applications to be capable of handling multi-graded relevance data. Most of today's recommender social web applications o er the possibility to rate objects with di erent levels of relevance. Nevertheless most performance measures in Information Retrieval and recommender systems are based on the assumption that retrieved objects (e. g...

This paper describes our approaches in NTCIR-13 on short text conversation(STC) task (Chinese). For retrieval-based method, we propose a response matching and ranking model which takes not only the text information into account, but also considers visual features of images corresponding to the text. For generation-based method, we propose the emotion-aware neural response generation model. Base...

We consider an online learning to rank setting in which, at each round, an oblivious adversary generates a list of m documents, pertaining to a query, and the learner produces scores to rank the documents. The adversary then generates a relevance vector and the learner updates its ranker according to the feedback received. We consider the setting where the feedback is restricted to be the relev...

Nowadays social media are important tools for web resource discovery. The performance and capabilities of web searches are vital, especially search results from social research paper bookmarking. This paper proposes a new algorithm for ranking method that is a combination of similarity ranking with paper posted time or CSTRank. The paper posted time is static ranking for improving search result...