TAC 2009
Related Papers
Learning to Link Entities with Knowledge Base
This paper address the problem of entity link- ing. Specifically, given an entity mentioned in unstructured texts, the task is to link this entity with an entry stored in the …...
A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization
AbstractSupervised learning methods and LDA based topic model have been successfully applied in the field of multi-document summarization. In this paper, we propose a novel supervised approach that can incorporate …...
Summarization Evaluation in the Absence of Human Model Summaries Using the Compositionality of Word Embeddings
AbstractWe present a new summary evaluation approach that does not require human model summaries. Our approach exploits the compositional capabilities of corpus-based and lexical resource-based word embeddings to develop the …...
SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy
AbstractMost work on multi-document summarization has focused on generic summarization of information present in each individual document set. However, the under-explored setting of update summarization, where the goal is to …...
GeSERA: General-domain Summary Evaluation by Relevance Analysis
AbstractWe present GeSERA, an open-source improved version of SERA for evaluating automatic extractive and abstractive summaries from the general domain. SERA is based on a search engine that compares candidate …...