In this paper, we present a new ranking scheme, collaborative ranking (CR). In contrast to traditional non-collaborative ranking scheme which solely relies on the strengths of isolated queries and one stand-alone ranking algorithm, the new scheme integrates the strengths from multiple collaborators of a query and the strengths from multiple ranking algorithms. We elaborate three specific forms ...

In this paper we describe our participation in INEX 2009 in the Ad Hoc Track, the Book Track, and the Entity Ranking Track. In the Ad Hoc track we investigate focused link evidence, using only links from retrieved sections. The new collection is not only annotated with Wikipedia categories, but also with YAGO/WordNet categories. We explore how we can use both types of category information, in t...

We query the pictures of Yahoo! News for persons and objects by using the accompanying news captions as an indexing annotation. Our aim is to find these pictures on top of the answer list in which the sought persons or objects are most prominently present. We demonstrate that an appearance or content model based on syntactic, semantic and discourse analysis of the short news text is only useful...

We present work on building a global long-tailed ranking of entities across multiple languages using Wikipedia and Freebase knowledge bases. We identify multiple features and build a model to rank entities using a ground-truth dataset of more than 10 thousand labels. The final system ranks 27 million entities with 75% precision and 48% F1 score. We provide performance evaluation and empirical e...

Log information describing the items the users have selected from the set of answers a query engine returns to their queries constitute an excellent form of indirect user feedback that has been extensively used in the web to improve the effectiveness of search engines. In this work we study how the logs can be exploited to improve the ranking of the results returned by an entity search engine. ...

In text-based semantic analysis the task of named entity linking (NEL) establishes the fundamental link between unstructured data elements and knowledge base entities. The increasing number of applications complementing web data via knowledge base entities has led to a rich toolset of NEL frameworks [4,7]. To resolve linguistic ambiguities, NEL relates available context information via statisti...

On the Web of Data, entities are often interconnected in a way similar to web documents. Previous works have shown how PageRank can be adapted to achieve entity ranking. In this paper, we propose to exploit locality on the Web of Data by taking a layered approach, similar to hierarchical PageRank approaches. We provide justifications for a two-layer model of the Web of Data, and introduce DING ...

Wikipedia is a useful source of knowledge that has many applications in language processing and knowledge representation. The Wikipedia category graph can be compared with the class hierarchy in an ontology; it has some characteristics in common as well as some differences. In this paper, we present our approach for answering entity ranking queries from the Wikipedia. In particular, we explore ...

The deployment of Web 2.0 technologies has led to rapid growth of various opinions and reviews on the web, such as reviews on products and opinions about people. Such content can be very useful to help people find interesting entities like products, businesses and people based on their individual preferences or tradeoffs. Most existing work on leveraging opinionated content has focused on integ...

Commercial search systems have recently begun using entity cards to support their ranked results lists. In this work, we propose an automated method for entity card building. We model this problem as a learning to rank approach applied to entity attributes. We introduce a new set of features that utilizes semantic information about entities as well as information from top-ranked documents using...