Computer Science

The idea to present the paper on Expert System (ES) approach to improve agriculture decision which is intended to be used by rural farmers and decision makers. In the world of computer science there are many expert system has been developed for agriculture but this paper particularly discussed the problem facing by former in rural areas in India due to lack of education and awareness of immerging technology. The Expert System in agriculture is a simple and based on agriculture related problem solving models; include Diagnostics model, Prediction model and Form Management model. This expert system will allow former to interact with Expert System (ES) and can get the solution over the defined problem. It uses the stored knowledge of step by step solution over the problem, in database which is the captured expertise of experience people and doctorate people in the field of agriculture through IF-THEN rules and facts, which are used to solve problem by answering question asked by user through interface which will be GUI based Audio, Video and Image based interaction between former and ES. For example, 1) In pest control, which pesticide use to spray by only questioning symptoms of disease. 2) Selection of fertilizer and quantity by describing the health of crop.

For a broad-topic and ambiguous query, different users may have different search goals when they submit it to a search engine. The inference and analysis of user search goals can be very useful in improving search engine relevance and user experience. In this paper, we propose a novel approach to infer user search goals by analyzing search engine query logs. First, we propose a framework to discover different user search goals for a query by clustering the proposed feedback sessions. Feedback sessions are constructed from user click-through logs and can efficiently reflect the information needs of users. Second, we propose a novel approach to generate pseudo-documents to better represent the feedback sessions for clustering. Finally, we propose a new criterion "Classified Average Precision (CAP)" to evaluate the performance of inferring user search goals. Experimental results are presented using user click-through logs from a commercial search engine to validate the effectiveness of our proposed methods.

Search reranking is considered as a best and basic approach to enhance recovery accuracy. The recordings are recovered utilizing the related literary data, for example, encompassing content from the website page. The execution of such frameworks basically depends on the importance between the content and the recordings. In any case, they may not generally coordinate all around ok, which causes boisterous positioning results. For example, outwardly comparative recordings may have altogether different positions. So reranking has been proposed to tackle the issue. Video reranking, as a compelling approach to enhance the consequences of electronic video look however the issue is not paltry particularly when we are thinking about different elements or modalities for pursuit in video and video recovery. This paper proposes another sort of reranking calculation, the round reranking, that backings the common trade of data over numerous modalities for enhancing seek execution and takes after the rationality of solid performing methodology could gain from weaker ones.

This paper gives a brief overview of various videos recommendation and Re-ranking techniques. It presents an advice framework which has been created to study examination addresses in the field of news feature suggestion and personalization. The framework is concentrated around semantically advanced feature information that allow look into on semantic models for flexible intelligent frameworks. It is frequently conceivable to enhance the recovery execution by repositioning the examples. We proposed a re-positioning strategy that enhances the execution of semantic feature indexing and recovery by reassessing the scores of the shots by the homogeneity and the way of the feature they fit in with. Contradistinction with past works the proposed strategy gives a system to the re-positioning through the homogeneous circulation of feature shots content in a worldly arrangement.

It seems that there is no limit to the amount of data we need to store in our computers and also send these data to our friends and colleagues. For this purpose people tend to store a lot of files inside their storage. When the storage nears it's limit, then they try to reduce those files size to minimum by using data compression software's. Compression aims to represent an input data with least number of bits. In this paper we describe the Burrows-Wheeler Transform (BWT), a data compression technique which is the basis of some of the best compressor available today.