97,777 research outputs found
Towards Automatic Extraction of Social Networks of Organizations in PubMed Abstracts
Social Network Analysis (SNA) of organizations can attract great interest
from government agencies and scientists for its ability to boost translational
research and accelerate the process of converting research to care. For SNA of
a particular disease area, we need to identify the key research groups in that
area by mining the affiliation information from PubMed. This not only involves
recognizing the organization names in the affiliation string, but also
resolving ambiguities to identify the article with a unique organization. We
present here a process of normalization that involves clustering based on local
sequence alignment metrics and local learning based on finding connected
components. We demonstrate the application of the method by analyzing
organizations involved in angiogenensis treatment, and demonstrating the
utility of the results for researchers in the pharmaceutical and biotechnology
industries or national funding agencies.Comment: This paper has been withdrawn; First International Workshop on Graph
Techniques for Biomedical Networks in Conjunction with IEEE International
Conference on Bioinformatics and Biomedicine, Washington D.C., USA, Nov. 1-4,
2009; http://www.public.asu.edu/~sjonnal3/home/papers/IEEE%20BIBM%202009.pd
Topic modeling for entity linking using keyphrase
This paper proposes an Entity Linking system that applies a topic modeling ranking. We apply a novel approach in order to provide new relevant elements to the model. These elements are keyphrases related to the queries and gathered from a huge Wikipedia-based knowledge resourcePeer ReviewedPostprint (author’s final draft
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