Retrieving entities inside documents instead of documents or web pages themselves has become an active topic in both commercial search systems and academic information retrieval research. Our method of entity retrieval is based on a two-layer retrieval and extraction probability model (TREPM) for integrating document retrieval and entity extraction together. The document retrieval layer finds supporting documents from the corpus, and the entity extraction layer extracts the right entities from those supporting documents. We theoretically demonstrate that the entity extraction problem can be represented as TREPM model. The TREPM model can reduce the overall retrieval complexity while keeping high accuracy of locating target entities. The exp...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
The immense scale of the Web has rendered itself as a huge repository storing information about vari...
Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is n...
Retrieving entities inside documents instead of documents or web pages themselves has become an acti...
Retrieving entities inside documents instead of documents or web pages themselves has become an acti...
Fang, HuiIn the past decade, the prosperity of the World Wide Web has led to fast explosion of info...
Retrieving entities from inside of documents, instead of searching for documents or web pages themse...
Entity retrieval finds the relevant results for a user’s information needs at a finer unit called “e...
Retrieving entities from inside of documents, instead of searching for documents or web pages themse...
in Entity Track in TREC2009. The task and data are both new this year. In our work, an improved two-...
The goal of this work is to leverage cross-document entity relationships for improved understanding ...
As the Web has evolved into a data-rich repository, with the standard "page view," current search en...
Our goal in participating in the TREC 2009 Entity Track was to study whether relation extraction te...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
The immense scale of the Web has rendered itself as a huge repository storing information about vari...
Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is n...
Retrieving entities inside documents instead of documents or web pages themselves has become an acti...
Retrieving entities inside documents instead of documents or web pages themselves has become an acti...
Fang, HuiIn the past decade, the prosperity of the World Wide Web has led to fast explosion of info...
Retrieving entities from inside of documents, instead of searching for documents or web pages themse...
Entity retrieval finds the relevant results for a user’s information needs at a finer unit called “e...
Retrieving entities from inside of documents, instead of searching for documents or web pages themse...
in Entity Track in TREC2009. The task and data are both new this year. In our work, an improved two-...
The goal of this work is to leverage cross-document entity relationships for improved understanding ...
As the Web has evolved into a data-rich repository, with the standard "page view," current search en...
Our goal in participating in the TREC 2009 Entity Track was to study whether relation extraction te...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
When humans explain complex topics, they naturally talk about involved entities, such as people, loc...
The immense scale of the Web has rendered itself as a huge repository storing information about vari...
Entity Ranking (ER) is a recently emerging search task in Information Retrieval, where the goal is n...