We describe our participation in the INEX 2008 Entity Ranking and Link-the-Wiki tracks. We provide a detailed account of the ideas underlying our approaches to these tasks. For the Link-the-Wiki track, we also report on the results and findings so far.

As the Web has evolved into a data-rich repository, with the standard “page view,” current search engines are becoming increasingly inadequate for a wide range of query tasks. While we often search for various data “entities” (e.g., phone number, paper PDF, date), today’s engines only take us indirectly to pages. While entities appear in many pages, current engines only find each page individua...

Triple stores have long provided RDF storage as well as data access using expressive, formal query languages such as SPARQL. The new end users of the Semantic Web, however, are mostly unaware of SPARQL and overwhelmingly prefer imprecise, informal keyword queries for searching over data. At the same time, the amount of data on the Semantic Web is approaching the limits of the architectures that...

This paper focuses on the Web-based English-Chinese OOV term translation pattern, and emphasizes particularly on the translation selection strategy based on the fusion of multiple features and the ranking mechanism based on Ranking Support Vector Machine (Ranking SVM). By utilizing the CoNLL2003 corpus for the English Named Entity Recognition (NER) task and selected new terms, the experiments b...

Entity linking refers to a string in text corresponding entities knowledge base through candidate entity generation and ranking. It is of great significance some NLP (natural language processing) tasks, such as question answering. Unlike English linking, Chinese requires more consideration due the lack spacing capitalization sequences ambiguity characters words, which evident certain scenarios....

With millions of articles in multiple languages, Wikipedia has become the de-facto source of reference on the Internet today. Each article on Wikipedia contains encyclopedic information about various topics (people, events, inventions, etc.) and implicitly represents an entity. Extracting the most important facts about such entity will help users to find desired information more quickly and eff...

Named Entity Recognition became the basis of many Natural Language Processing applications. However, the existing coarsegrained named entity recognizers are insufficient for complex applications such as Question Answering, Internet Search engines or Ontology population. In this paper, we propose a domain distribution approach according to which names which occur in the same domains belong to th...

Named Entity Linking (nel) grounds entity mentions to their corresponding node in a Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity mentions in text to Wikipedia pages. Such systems typically search for candidate entities and then disambiguate them, returning either the best candidate or nil. However, comparison has focused on disambiguation accuracy, ma...

Entity Linking (EL) is a fundamental technology in Natural Language Processing and Knowledge Engineering. Previous works mainly focus on linking mentioned names recognized in news or articles to knowledge base. However, in social network, user-generated content is quite different from typical news text. Users sometimes use words more informally, even create new words. One entity may have differ...

The related applications are limited due to the static characteristics on existing relatedness calculation algorithms. We proposed a method aiming to efficiently compute the dynamic relatedness between Chinese entity-pairs, which changes over time. Our method consists of three components: using cooccurrence statistics method to mine the co-occurrence information of entities from the news texts,...