A video analysis on user feedback based recommendation using A-FP hybrid algorithm

摘要

Video mining is an unsupervised finding of pattern in audio-visual content and also offers the optimized search based on event of interest associated to the target search over the search engine. Video mining is dawn related to other mining. Yet, the objective of existing search is to fetch a specific video from large database. Hence, our proposed goal is to retrieving of user's requisite video based on an event is the major core problem in video mining. This paper propounds a new feedback relevance based video retrieval uses a hybrid of Apriori and Frequent Pattern (A-FP) algorithm creates a new methodology that gives the design of the learning. The A-FP algorithm desire to elicitation the most frequent item search which is pragmatic to the user. It also affords scalable solution for generalizing efficient and highly ambiguous user expected video search.