Posts tagged Wikipedia

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Learning to Explain Entity Relationships in Knowledge Graphs

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We study the problem of explaining relationships between pairs of knowledge graph entities with human-readable descriptions. Our method 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. We model this task More >

wsdm 2015

Fast and Space-Efficient Entity Linking in Queries

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Entity linking deals with identifying entities from a knowledge base in a given piece of text and has become a fundamental building block for web search engines, enabling numerous downstream improvements from better document ranking to enhanced search results pages. A key problem in the context of web search queries More >

Yahoo Labs

Linking queries to entities

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I’m happy to announce we’re releasing a new test collection for entity linking for web queries (within user sessions) to Wikipedia. About half of the queries in this dataset are sampled from Yahoo search logs, the other half comes from the TREC Session track. Check out the L24 dataset More >

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Entity Linking and Retrieval Tutorial @ SIGIR 2013 – Slides, Code, and Bibliography

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The material for our “Entity Linking and Retrieval” tutorial (with Krisztian Balog and Daan Odijk) for SIGIR 2013 has been updated and is available online on GitHub (slides), Dropbox (slides), Mendeley, and CodeAcademy. All material is summarized at the webpage for the tutorial: http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/. See my other blogpost for a brief summary.

Semantic TED

Multilingual Semantic Linking for Video Streams: Making “Ideas Worth Sharing” More Accessible

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This paper describes our (winning!) submission to the Developers Challenge at WoLE2013, “Doing Good by Linking Entities.” We present a fully automatic system – called “Semantic TED” – which provides intelligent suggestions in the form of links to Wikipedia articles for video streams in multiple More >

Entity Linking

Entity Linking and Retrieval Tutorial – Slides, Code, and Bibliography

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The material for our “Entity Linking and Retrieval” tutorial (with Krisztian Balog and Daan Odijk) for WWW2013 is now available online on GitHub, Mendeley, and CodeAcademy. All material is summarized at the webpage for the tutorial: http://ejmeij.github.io/entity-linking-and-retrieval-tutorial/. See my other blogpost for a brief summary.

Example entity linking for tweets, to support tweets summarization

Personalized Time-Aware Tweets Summarization

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To appear as full paper at SIGIR 2013.

In this paper we focus on selecting meaningful tweets given a user’s interests. Specifically, we consider the task of time-aware tweets summarization, based on a user’s history and collaborative social influences from “social circles.” Continue reading “Personalized Time-Aware Tweets Summarization” »

Second screen

Feeding the Second Screen: Semantic Linking based on Subtitles

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Television is changing. Increasingly, broadcasts are consumed interactively. This allows broadcasters to provide consumers with additional background information that they may bookmark for later consumption. Continue reading “Feeding the Second Screen: Semantic Linking based on Subtitles” »

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Hadoop code for TREC KBA

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I’ve decided to put some of the Hadoop code I developed for the TREC KBA task online. It’s available on Github: https://github.com/ejmeij/trec-kba. In particular, it provides classes to read/write topic files, read/write run files, and expose the documents in the Thrift files as Hadoop-readable objects (‘ThriftFileInputFormat’) to be used as input to More >

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