We describe our participation in the INEX 2008 Entity Ranking track. We develop a generative language modeling approach for the entity ranking and list completion tasks. Our framework comprises the following components: (i) entity and (ii) query language models, (iii) entity prior, (iv) the probability of an entity for a given category, and (v) the probability of an entity given another entity....

Information discovery on the Web has so far been dominated by keyword-based document search. However, recent years have witnessed arising needs from Web users to search for named entities, e.g., finding all Silicon Valley companies. With existing Web search engines, users have to digest returned Web pages by themselves to find the answers. Entity search has been introduced as a solution to this...

We examine the problem of entity ranking using opinions expressed in users' reviews. There is a massive development of opinions and reviews on the web, which includes reviews of products and services, and opinions about events and persons. For products especially, there are thousands of users' reviews, that consumers usually consult before proceeding in a purchase. In this study we are followin...

In this paper, we present FRDC's system at participating in the cross-lingual entity linking (CLEL) tasks for the NIST Text Analysis Conference (TAC) Knowledge Base Population (KBP2013) track. We propose a joint approach for mention expansion, disambiguation, and clustering. In particular, we adopt a lexicon and rule based method for entity classification, a collaborative acronym expansion meth...

This paper describes experiments carried out at NiCT for the TREC 2010 Entity track. Our studies mainly focus on improving the NE Extraction and Ranking Entity modules, both of them play vital roles in Related Entity Finding system. In our last year’s system, only a Named Entity Recognition tool is used to extract entities that match coarse-grained types of target entities such as organization,...

This paper describes the participation of the INRIA group in the INEX 2007 XML entity ranking and ad hoc tracks. We developed a system for ranking Wikipedia entities in answer to a query. Our approach utilises the known categories, the link structure of Wikipedia, as well as the link co-occurrences with the examples (when provided) to improve the effectiveness of entity ranking. Our experiments...

User-generated content often provides more information than just textual data, i.e. tags or annotations are added to label data, in discussions users can comment on the data, and links exist not only between pages, but also between users and annotations. In this paper we explore the use of annotations in the form of categories to find entities or information in Wikipedia. Main differences betwe...

: Entity linking has received much more attention. The purpose of entity linking is to link the mentions in the text to the corresponding entities in the knowledge base. Most work of entity linking is aiming at long texts, such as BBS or blog. Microblog as a new kind of social platform, entity linking in which will face many problems. In this paper, we divide the entity linking task into two pa...