Call For Paper Volume:7 Issue:5 May'2020 |

Mining Text Data Using Side Information: A Survey

Publication Date : 02/05/2016

Author(s) :

Mr. Shekhar S. Patil , Prof. R. B. Wagh.

Conference Name :
International Conference on Recent Trends in Engineering and Technology

Abstract :

This In lots of textual content mining applications, side Information are to be had in conjunction with the text files. Such side information may additionally be of different types, which includes file provenance information, the hyperlinks inside the document, user get right of entry to behavior from web logs, or different non-textual attributes which can be embedded into the text record. Such attributes may include a super amount of information for clustering functions. However, the relative significance of this side information can be tough to estimate, mainly whilst a number of the facts is noisy. In such cases, it is able to be volatile to incorporate side information into the mining technique, due to the fact it is able to either improve the pleasant of the representation for the mining system, or can add noise to the manner. therefore, we want a principled manner to carry out the mining process, to be able to maximize the advantages from using this aspect data. The COATES algorithm iscombines classical partitioning algorithms with probabilistic models which create a powerful clustering approach.By using this methodone can extend the approach to the classification problem.

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