DESIGN OF AN INTEGRATED QUERY PROCESSING SYSTEM FOR SOCIAL WEB

Awarded to Charu Virmani in 2018 under the Supervision of Dr. Anuradha and Dr. Dimple Juneja

The work proposes Hybrid Integrated Autonomous Social Network (HIASN), a novel architecture for integrating the profiles of the user in an effective manner. A clustering mechanism termed as Hybrid Ensemble k-Means Hierarchical Agglomerative clustering (HEKHAC), is also being proposed which uses user’s publicly available attributes to make optimal clusters to retrieve the desired information from the query written in a natural language. Another significant contribution is made through Query Processing in Social Networks Aggregator (QPSNA) which includes four modules namely, Query Processing System (QPS), Content Based Semantic Matcher Maker (CBSMM), Machine Learning Mechanism (MLM) and Ranking of results to answer user’s query. QPSNA extracts entity that is then mapped it to its semantic meaning, identifies user preferred profiles and improves upon the user’s preference by ranking the profiles. The proposed system integrates several social websites together and responds to a user’s query; extracting the relevant data as specified in query written in a natural language from multiple social networks and presenting data appropriately as result; thereby helping users who belong to multiple networks manage diverse profiles across multiple social networking sites. The proposed system will maintain several accounts at one place and extracts the relevant publicly available data. It also aims to offer an improvement over keyword searching by using NLP techniques. Read more at ......

Cite this work as "Virmani, C., Juneja, D., & Pillai, A. (2018). Design of Query Processing System to Retrieve Information from Social Network using NLP. KSII Transactions on Internet & Information Systems, 12(3)."