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https://ptsldigital.ukm.my/jspui/handle/123456789/476554| Title: | Extraction of nationality from crime news |
| Authors: | Abdulrahman Alkaff (P50149) |
| Supervisor: | Masnizah Mohd, Dr. |
| Keywords: | Universiti Kebangsaan Malaysia -- Dissertations |
| Issue Date: | 2012 |
| Description: | Most of the crimes committed today are reported on the Internet through news, blogs and social networking sites. These sources have provided a huge amount of crime data, presenting a need for a means to extract useful and significant information. A few works have been done on methods of extracting features of crimes, such as personality characteristics of crime organization members, locations and weapons used. However, none of these works resulted in information related to nationality or provided additional references to identify the nationalities of the suspects, victims or witnesses. In a community like Malaysia, that consists of many different nationalities, with many foreign tourists, immigrant workers, and international students, presenting a need to extract the nationality information from crime news and their references to give a different value for advance analysing, collecting and connecting data. In addition to help in the field of journalism and research. In this research, the evaluation of Direct and Indirect extraction of nationality from crime news, along with the additional references to identify the nationalities of suspects, victims and witnesses is presented. Named entity recognition using gazetteers and rule-based extraction are used, in addition to co-reference resolution to link the references. The text data set used was collected from the Malaysian National News Agency (Bernama). The proposed approach was tested, evaluated and compared to manual extraction system. The results indicate that the proposed approach is able to extract most information related to nationality from crimes news and identify the additional information references.,Certification of Master's / Doctoral Thesis" is not available |
| Pages: | 82 |
| Call Number: | QA76.9.N38A567 2012 3 tesis |
| Publisher: | UKM, Bangi |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_119398+SOURCE1+SOURCE1.0.PDF Restricted Access | 607.54 kB | Adobe PDF |  View/Open |
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