-
Carmel, E.; Crawford, S.; Chen, H.: Browsing in hypertext : a cognitive study (1992)
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- Source
- IEEE transactions on systems, man and cybernetics. 22(1992) no.5, S.865-884
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Leroy, G.; Chen, H.: Genescene: an ontology-enhanced integration of linguistic and co-occurrence based relations in biomedical texts (2005)
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- Abstract
- The increasing amount of publicly available literature and experimental data in biomedicine makes it hard for biomedical researchers to stay up-to-date. Genescene is a toolkit that will help alleviate this problem by providing an overview of published literature content. We combined a linguistic parser with Concept Space, a co-occurrence based semantic net. Both techniques extract complementary biomedical relations between noun phrases from MEDLINE abstracts. The parser extracts precise and semantically rich relations from individual abstracts. Concept Space extracts relations that hold true for the collection of abstracts. The Gene Ontology, the Human Genome Nomenclature, and the Unified Medical Language System, are also integrated in Genescene. Currently, they are used to facilitate the integration of the two relation types, and to select the more interesting and high-quality relations for presentation. A user study focusing on p53 literature is discussed. All MEDLINE abstracts discussing p53 were processed in Genescene. Two researchers evaluated the terms and relations from several abstracts of interest to them. The results show that the terms were precise (precision 93%) and relevant, as were the parser relations (precision 95%). The Concept Space relations were more precise when selected with ontological knowledge (precision 78%) than without (60%).
- Date
- 22. 7.2006 14:26:01
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Hu, D.; Kaza, S.; Chen, H.: Identifying significant facilitators of dark network evolution (2009)
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- Abstract
- Social networks evolve over time with the addition and removal of nodes and links to survive and thrive in their environments. Previous studies have shown that the link-formation process in such networks is influenced by a set of facilitators. However, there have been few empirical evaluations to determine the important facilitators. In a research partnership with law enforcement agencies, we used dynamic social-network analysis methods to examine several plausible facilitators of co-offending relationships in a large-scale narcotics network consisting of individuals and vehicles. Multivariate Cox regression and a two-proportion z-test on cyclic and focal closures of the network showed that mutual acquaintance and vehicle affiliations were significant facilitators for the network under study. We also found that homophily with respect to age, race, and gender were not good predictors of future link formation in these networks. Moreover, we examined the social causes and policy implications for the significance and insignificance of various facilitators including common jails on future co-offending. These findings provide important insights into the link-formation processes and the resilience of social networks. In addition, they can be used to aid in the prediction of future links. The methods described can also help in understanding the driving forces behind the formation and evolution of social networks facilitated by mobile and Web technologies.
- Date
- 22. 3.2009 18:50:30
