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Identification of User Aware Rare Sequential Pattern in Document Stream- An Overview

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Identification of User Aware Rare Sequential Pattern in Document Stream- An Overview


Rajeshri R. Shelke



Rajeshri R. Shelke "Identification of User Aware Rare Sequential Pattern in Document Stream- An Overview" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4, June 2019, pp.1340-1342, URL: https://www.ijtsrd.com/papers/ijtsrd24008.pdf

Documents created and distributed on the Internet are ever changing in various forms. Most of existing works are devoted to topic modeling and the evolution of individual topics, while sequential relations of topics in successive documents published by a specific user are ignored. In order to characterize and detect personalized and abnormal behaviours of Internet users, we propose Sequential Topic Patterns (STPs) and formulate the problem of mining User-aware Rare Sequential Topic Patterns (URSTPs) in document streams on the Internet. They are rare on the whole but relatively frequent for specific users, so can be applied in many real-life scenarios, such as real-time monitoring on abnormal user behaviours. Here present solutions to solve this innovative mining problem through three phases: pre-processing to extract probabilistic topics and identify sessions for different users, generating all the STP candidates with (expected) support values for each user by pattern-growth, and selecting URSTPs by making useraware rarity analysis on derived STPs. Experiments on both real (Twitter) and synthetic datasets show that our approach can indeed discover special users and interpretable URSTPs effectively and efficiently, which significantly reflect users’ characteristics.

Web mining, sequential patterns, document streams, rare events, pattern-growth.


IJTSRD24008
Volume-3 | Issue-4, June 2019
1340-1342
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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