01520nas a2200157   4500008004100000245010200041210006900143260001200212300001000224490000700234520099000241100002701231700002701258700002101285856005601306       2018                        eng d00aEfficient Management of Community Question Answering Sites using Improved Spectral Clustering –0 aEfficient Management of Community Question Answering Sites using  c04/2018  a76-840 v163 a<p>Community Question-Answering(CQA) sites are the major platform where posts are generated by peers in the form of questions and answers for information seeking in online environments. In general, multiple posts are created by different users on a particular topic or subject. Large number of posts raises the difficulties in information management of these sites. A number of approaches are suggested in recent research work for efficient management of data for CQA sites. Many of the existing approaches have suggested use of clustering techniques for managing the CQA sites, but ignored the tagging data (user tags) of the posts. In this paper, an improved spectral clustering technique is derived based on similarity measures for text processing (SMTP) and utilized for clustering the posts considering the tagging data available on CQA sites. A specialized data structure, namely, folksonomy is developed for clustering using the relationship between tags, posts and users.</p>
1 aSingh, Abhishek, Kumar1 aNagwani, Naresh, Kumar1 aPandey, Sudhakar  uhttp://dline.info/fpaper/jdim/v16i2/jdimv16i2_3.pdf