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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.
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.
Fast and Space-Efficient Entity Linking for Queries
TLDR
This paper proposes a probabilistic model that leverages user-generated information on the web to link queries to entities in a knowledge base and significantly outperforms several state-of-the-art baselines while being able to process queries in sub-millisecond times---at least two orders of magnitude faster than existing systems.
Overview of RepLab 2014: Author Profiling and Reputation Dimensions for Online Reputation Management
TLDR
The organisation and results of RepLab 2014 are described, which focused on two new tasks: reputation dimensions classification and author profiling, which complement the aspects of reputation analysis studied in the previous campaigns.
Learning to Explain Entity Relationships in Knowledge Graphs
TLDR
This work extracts and enriches sentences that refer to an entity pair from a corpus and ranks the sentences according to how well they describe the relationship between the entities.
Personalized time-aware tweets summarization
TLDR
A time-aware user behavior model is proposed, the Tweet Propagation Model (TPM), in which dynamic probabilistic distributions over interests and topics are inferred and an iterative optimization algorithm for selecting tweets is proposed.
Overview of RepLab 2012: Evaluating Online Reputation Management Systems
TLDR
This paper summarizes the goals, organization and results of the RepLab competitive evaluation campaign for Online Reputation Management Systems (RepLab 2012), which asked participant systems to annotate types of information on tweets containing the names of several companies.
People searching for people: analysis of a people search engine log
TLDR
Based on an extensive analysis of the logs of a search engine geared towards finding people, a classification scheme for people search is proposed at three levels: queries, sessions, and users.
Dynamic Collective Entity Representations for Entity Ranking
TLDR
This work proposes a method for constructing dynamic collective entity representations that collects entity descriptions from a variety of sources and combines them into a single entity representation by learning to weight the content from different sources that are associated with an entity for optimal retrieval effectiveness.
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