Summarization algorithms performance for topic clustered twitter microblogs
This paper discusses an approach that would allow for the condensation of a bodyof Twitter microblogs into a wieldy size by extracting the topics being discussed in acorpus of tweets using Latent Dirichlet Allocation (LDA). The approach presents theoutput into a human readable summary using the Phra...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | text |
| منشور في: |
Archīum Ateneo
2018
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://archium.ateneo.edu/theses-dissertations/58 http://rizalls.lib.admu.edu.ph/#section=resource&resourceid=1564945654&currentIndex=0&view=fullDetailsDetailsTab |
| الوسوم: |
إضافة وسم
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| الملخص: | This paper discusses an approach that would allow for the condensation of a bodyof Twitter microblogs into a wieldy size by extracting the topics being discussed in acorpus of tweets using Latent Dirichlet Allocation (LDA). The approach presents theoutput into a human readable summary using the Phrase Reinforcement (PR)algorithm. The average F-measure score of this method exceeds those of othermethods when evaluated against human-made summaries. Results also suggest thatLDA together with PR is more robust against noisier datasets than the other testedmethods. This solution would help utilize Twitter into a tool not only for sharing ofexperiences but also a tool for gathering the state of the population. Decision makerscan use this solution to make informed action. |
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