Title :
Summarizing Online Discussions by filtering posts
Author :
Altantawy, Mohamed ; Rafea, Ahmed ; Aly, Sherif
Author_Institution :
American Univ. in Cairo, Cairo, Egypt
Abstract :
In this paper, we attempt to summarize online discussions by filtering posts. Selecting the highly related posts from the discussion boards leads to a summarized version of the discussion. Online discussion summarizer (ODS) is based on unsupervised information retrieval techniques. Four features are used in the summarization function; which are the term frequency inverse post frequency, title term frequency, description term frequency and author reputation. This paper shows that combining the four features in the same function results in higher accuracy than using each alone. ODS was able to summarize online discussions with an accuracy of 72%, precession of 83% and recall of 62%.
Keywords :
information retrieval; author reputation; description term frequency; discussion boards; online discussion summarizer; post filtering; term frequency inverse post frequency; title term frequency; unsupervised information retrieval techniques; Data mining; Data preprocessing; Filtering; Filters; Frequency; Information retrieval; User-generated content; Information Retrieval; Social Media; Text Summarization;
Conference_Titel :
Information Reuse & Integration, 2009. IRI '09. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-4114-3
Electronic_ISBN :
978-1-4244-4116-7
DOI :
10.1109/IRI.2009.5211592
