Integrating document features for entity ranking

Zhu, Jianhan; Song, Dawei and Rüger, Stefan (2008). Integrating document features for entity ranking. In: Focused Access to XML Documents, pp. 336–347.

DOI: https://doi.org/10.1007/978-3-540-85902-4_29

Abstract

The Knowledge Media Institute of the Open University participated in the entity ranking and entity list completion tasks of the Entity Ranking Track in INEX 2007. In both the entity ranking and entity list completion tasks, we have considered document features in addition to a basic document content based relevance model. These document features include categorizations of documents, relevance of category names to the query, and hierarchical relations between categories. Furthermore, based on our TREC2006 and 2007 expert search approach, we applied a co-occurrence based entity association discovery model to the two tasks based on the assumption that relevant entities often co-occur with query terms or given relevant entities in documents. Our initial experimental results show that, by considering the predefined category, its children and grandchildren in the document content based relevance model, the performance of our entity ranking approach can be significantly improved. Consideration of the predefined category’s parents, a category name based relevance model, and the co-occurrence model is not shown to be helpful in entity ranking and list completion, respectively.

Viewing alternatives

Look up in Google Scholar

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions
No digital document available to download for this item

Item Actions

Export

About

CORE (COnnecting REpositories)

Recommendations