Intelligence and Security Informatics: First NSF/NIJ by Aixin Sun, Myo-Myo Naing, Ee-Peng Lim, Wai Lam (auth.),
By Aixin Sun, Myo-Myo Naing, Ee-Peng Lim, Wai Lam (auth.), Hsinchun Chen, Richard Miranda, Daniel D. Zeng, Chris Demchak, Jenny Schroeder, Therani Madhusudan (eds.)
Since the tragic occasions of September eleven, 2001, teachers were known as on for attainable contributions to investigate when it comes to nationwide (and most likely internat- nal) defense. As one of many unique founding mandates of the nationwide technological know-how beginning, mid- to long term nationwide defense examine within the parts of inf- mation applied sciences, organizational experiences, and security-related public coverage is significantly wanted. In a manner just like how clinical and organic study has confronted signi?cant info overload and but additionally large possibilities for brand spanking new inno- tion, legislations enforcement, legal research, and intelligence groups are dealing with an analogous problem. We think, just like “medical informatics” and “bioinf- matics,” that there's a urgent have to increase the technological know-how of “intelligence and safeguard informatics” – the research of the use and improvement of complicated details applied sciences, platforms, algorithms and databases for nationwide se- rity similar applications,through an built-in technological,organizational,and policy-based strategy. We think energetic “intelligence and safety informatics” examine might help increase wisdom discovery and dissemination and increase details s- ring and collaboration throughout legislations enforcement groups and between aca- mics, neighborhood, nation, and federal firms, and undefined. Many current laptop and knowledge technological know-how options must be reexamined and tailored for - tional safeguard purposes. New insights from this exact area may bring about signi?cant breakthroughs in new info mining, visualization, wisdom - nagement, and data safety concepts and systems.
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Extra info for Intelligence and Security Informatics: First NSF/NIJ Symposium, ISI 2003, Tucson, AZ, USA, June 2–3, 2003 Proceedings
NameGenderizer¹: This module returns the most likely gender for a given name based on frequency of assignment of the name to males or females. A major advantage of the technologies developed by LAS is that a measure of similarity between name forms is computed and used to return names in order of their degree of similarity to the query term. 1 in the Appendix. 3 Named Entity Extraction The task of named entity recognition and extraction is to identify strings in text that represent names of people, organizations, and places.
Returns are presented in ranked order. This approach is particularly effective when name entries have been drawn from oral sources, such as telephone conversations. NameGenderizer¹: This module returns the most likely gender for a given name based on frequency of assignment of the name to males or females. A major advantage of the technologies developed by LAS is that a measure of similarity between name forms is computed and used to return names in order of their degree of similarity to the query term.
14], , , ). Results in some cases have been very good, with F-measure scores exceeding 94%, even for systems gathering information from the least computationally expensive sources, such as punctuation, dictionary look-up, and part-of-speech taggers . Borthwick et al.  found that by training their system on outputs tagged by hand-built systems (such as SRA’s NameTag extractor), scores improved to better than 97%, exceeding the F-measure scores of hand-built systems alone, and rivaling scores of human annotators.