The present study investigates the problem of sorting search result by relevance. The new algorithm based on iterative procedural Internet search is developed. The aim of the study was to improve the existing algorithm. Results show that applying the improved algorithm approximately doubles Normalized Discounted Cumulative Gain at k and therefore greatly decrease average time to find relevant documents in search results list.
Question Answering refers to the task of providing a matching answer for a given user’s natural-language question. We assume here that the received response from a Question Answering system is also given as a natural-language output. From this scenario the task is raised to validate if the received natural-language answer is valid w.r.t. the given question. In this paper, we will present our approach to compute the similarity of a question to the corresponding natural-language answer while using the features of the surface form of the question and the answer. Our metrics is the distinction between a matching answer and inappropriate answers to a given question. Hence, our research agenda is dedicated to improving the answer quality of Question Answering systems by using the natural-language representation of its input and output.
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