An Information Filtering Model for Research Library

摘要

In the present era information filtering is a major challenge for Libraries and Information Centers. With the flooding of Information in the web; searching to multiple journals and finding relevent papers from the heap of garbage papers is a major issue for researchers. A model is developed to provide information service based on artificial intelligence. This system would be capable to filter papers from multiple databases/ journals on the basis of relevancy priority. The model is based on neural network which is a part of Artificial Intelligence. The way human brain learns and stores information in several neurons, same method is adopted in this model. In this system key words with their corresponding document links and priority number would continuously be sorted in a logical table and stored to keep system uptodate. For this sorting process the model has been sharing the knowledge of human brains. First the Expert system is trained, after that the system has become smart enough to provide service to the user. It has been found that the model is providing better information filtering mechanism to the researcher of specific subject area. But learning of the system will be lifelong process. Experience will improve its intelligence gradually with time.