Topic Detection Using Clustering

Topic Detection Using Clustering

Topic Detection Using Clustering

Topic Detection Using Clustering Database Management dot net project report system takes co occurrence of terms into account which gives best result. This system can be useful for web crawlers and for web users.Email has been an efficient and popular communication mechanism as the topic detection-keyword clustering number of Internet user’s increase. In many security informatics applications it is important to detect deceptive communication in email. Click here to get complete Dot Net projects lists.

We consider topic detection-keyword clustering without any prior knowledge of category structure or possible categories. Keywords are extracted and clustered based on different similarity mea- sures using the induced k-bisecting clustering algorithm. Evaluation on Wikipedia articles shows that clusters of key- words correlate strongly with the Wikipedia categories of the articles.


The experimental Topic Detection Using Clustering dot net project report results suggest that topic identification by clustering a set of keywords works fairly well, using either of the investigated similarity measures. In the present experiment a recently proposed distribution of terms associated with a keyword clearly gives best results, but computation of the distribution is relatively expensive. The reason for this is the fact that co-occurrence of terms is (implicitly) taken into account. 

System Configuration:

H/W System Configuration:- 

System          : Pentium I3 Processor.
Hard Disk       : 500 GB.
Monitor          : Standard LED Monitor
Input Devices : Keyboard
Ram               : 4 GB

S/W System Configuration:-

Operating system              : Windows 7/8/10.
Available Coding Language : Dot Net and PHP
Database                          : MYSQL

Project Name Topic Detection Using Clustering
Project Category Dot Net
Project Cost 65$/ Rs 4999
Delivery Time 48 Hour
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