Academic Journal
Summarization algorithms performance for topic clustered twitter microblogs
| Τίτλος: | Summarization algorithms performance for topic clustered twitter microblogs |
|---|---|
| Συγγραφείς: | SANTOS, JOHN SIXTO G. |
| Πηγή: | Theses and Dissertations (All) |
| Στοιχεία εκδότη: | Archīum Ateneo |
| Έτος έκδοσης: | 2018 |
| Θεματικοί όροι: | Twitter, Corpora (Linguistics) -- Data processing, Natural language processing (Computer science), Cluster analysis -- Computer programs |
| Περιγραφή: | 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. |
| Τύπος εγγράφου: | text |
| Γλώσσα: | unknown |
| Relation: | http://rizalls.lib.admu.edu.ph/#section=resource&resourceid=1564945654¤tIndex=0&view=fullDetailsDetailsTab |
| Διαθεσιμότητα: | https://archium.ateneo.edu/theses-dissertations/58 http://rizalls.lib.admu.edu.ph/#section=resource&resourceid=1564945654¤tIndex=0&view=fullDetailsDetailsTab |
| Αριθμός Καταχώρησης: | edsbas.53FE1C90 |
| Βάση Δεδομένων: | BASE |
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