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Modal Logic
Formal models for expert finding in enterprise corpora
TLDR
This work presents two general strategies to expert searching given a document collection which are formalized using generative probabilistic models, and shows that the second strategy consistently outperforms the first. Expand
Using WordNet to Measure Semantic Orientations of Adjectives
TLDR
A graph-theoretic model of WordNet’s most important relation—synonymy—is investigated and measures that determine the semantic orientation of adjectives for three factors of subjective meaning are proposed. Expand
Click Models for Web Search
TLDR
This survey summarizes advances in modeling user click behavior on a web search engine result page and presents simple click models as well as more complex models aimed at improving search result ranking. Expand
Adding semantics to microblog posts
TLDR
This work proposes a novel method based on machine learning with a set of innovative features and is able to achieve significant improvements over all other methods, especially in terms of precision. Expand
Siamese CBOW: Optimizing Word Embeddings for Sentence Representations
TLDR
The Siamese Continuous Bag of Words model is presented, a neural network for efficient estimation of high-quality sentence embeddings and the robustness of theSiamese CBOW model is shown by evaluating it on 20 datasets stemming from a wide variety of sources. Expand
Overview of the TREC 2006 Blog Track
TLDR
The Blog track began this year, with the aim to explore the information seeking behaviour in the blogosphere, and a new large-scale test collection, namely the TREC Blog06 collection, has been created. Expand
Overview of RepLab 2013: Evaluating Online Reputation Monitoring Systems
TLDR
This paper summarizes the goals, organization, and results of the second RepLab competitive evaluation campaign for Online Reputation Management Systems RepLab 2013, which consists of more than 140,000 tweets annotated by a group of trained annotators supervised and monitored by reputation experts. Expand
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
TLDR
A sharp finite-time regret bound of order O(K log T) is proved on a very general class of dueling bandit problems that matches a lower bound proven in (Yue et al., 2012). Expand
Learning Latent Vector Spaces for Product Search
TLDR
A novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations and achieves its enhanced performance as it learns better product representations. Expand
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