This paper documents our experiments in six of the INEX 2008 tracks: Ad Hoc, Book Search, Entity Ranking, Interactive, Link theWiki, and XMLMining. We discuss our aims, experiments, results and findings for each of these tracks.

We describe our participation in the INEX 2009 Entity Ranking and Link-the-Wiki tracks. We provide a detailed account of the ideas underlying our approaches to these tasks.

This paper presents a method for the hierarchical classification of image galleries into a taxonomy. The proposed method links textual gallery metadata to Wikipedia pages and categories. Entity extraction from metadata, entity ranking, and selection of categories is based on Wikipedia and does not require labeled training data. The resulting system performs well above a random baseline, and ach...

• Entity ranking: topic consists of a keyword query (Q) and target categories (C) • List completion: the topic also specifies example entities (E) • Users often look for specific entities instead of documents mentioning them • Entities represented by their Wikipedia page • Introduction a general probabilistic framework for entity retrieval • Focus on the use of category information in a theoret...

Ranking of universities represents a complex endeavor which involves gathering, weighting, and analyzing diverse data. Emerging semantic technologies enable the Web of Data, a giant graph of interconnected information resources, also known as Linked Data. A recent community effort, Linking Open Data project, offers the possibility of accessing a large number of semantically described and linked...

We propose a local coherence model based on a convolutional neural network that operates over the entity grid representation of a text. The model captures long range entity transitions along with entity-specific features without loosing generalization, thanks to the power of distributed representation. We present a pairwise ranking method to train the model in an end-to-end fashion on a task an...

The goal of the entity track is to perform entity-oriented search tasks on the World Wide Web. Many user information needs would be better answered by specific entities instead of just any type of documents. The track defines entities as “typed search results”, “things”, represented by their homepages on the web. Searching for entities thus corresponds to ranking these homepages. The track ther...

In this paper, we formalize the task of finding a knowledge base entry that a given named entity mention refers to, namely entity linking, by identifying the most “important” node among the graph nodes representing the candidate entries. With the aim of ranking these entities by their “importance”, we introduce three degree-based measures of graph connectivity. Experimental results on the TACKB...

Searching for named entities has been the subject of many researches in information retrieval. In this paper, we seek to determine whether a named entity is of a given type and in what extent it is. We propose to address this issue by an unsupervised web oriented language modeling approach. In addition, we want to determine if this new information can be used to improve the ranking of candidate...

Entity profiling is the task of identifying and ranking descriptions of a given entity. The task may be viewed as one where the descriptions being sought are terms that need to be selected from a knowledge source (such as an ontology or thesaurus). In this case, entity profiling systems can be assessed by means of precision and recall values of the descriptive terms produced. However, recent ev...