Abstract: An automated interactive optimization method of short keyword queries for improving information retrieval from opaque (black box) search engines is disclosed. The method requires collecting data from several fact-checking websites, for creating dataset used for evaluation; estimating the relevance of posts/query results retrieved from a search engine to a given input document, by calculating the mean relevance error (MRE), based on estimating the minimal distance between words comprising both the retrieved posts and the input document; labeling a subset of claims for evaluation, by choosing a number of claims that gained the maximal and the minimal mean relevance error (MRE); and finding the most appropriate queries in order to retrieve the maximal number of relevant posts using an opaque search engine, by performing an interactive greedy search for the best word that should be added to the input query, for maximizing the corresponding posts retrieved by the search engine.

Abstract: An automated interactive optimization method of short keyword queries for improving information retrieval from opaque (black box) search engines is disclosed. The method requires collecting data from several fact-checking websites, for creating dataset used for evaluation; estimating the relevance of posts/query results retrieved from a search engine to a given input document, by calculating the mean relevance error (MRE), based on estimating the minimal distance between words comprising both the retrieved posts and the input document; labeling a subset of claims for evaluation, by choosing a number of claims that gained the maximal and the minimal mean relevance error (MRE); and finding the most appropriate queries in order to retrieve the maximal number of relevant posts using an opaque search engine, by performing an interactive greedy search for the best word that should be added to the input query, for maximizing the corresponding posts retrieved by the search engine.

Abstract: An automated interactive optimization method of short keyword queries for improving information retrieval from opaque (black box) search engines, according to which data including labeled claims from several fact-checking websites, is collected for creating dataset which is used for evaluation. The relevance of posts/query results retrieved from a search engine to a given input document, is estimated by calculating the mean relevance error (MRE), based on estimating the minimal distance between words comprising both the retrieved posts and the input document. A subset of claims is labeled for evaluation, by choosing a number of claims that gained the maximal and the minimal mean relevance error (MRE). The most appropriate keywords is found in order to retrieve the maximal number of relevant posts using an opaque search engine, by performing an interactive greedy search for the best word that should be added to the input query, for maximizing the corresponding posts retrieved by the search engine.

Abstract: An automated interactive optimization method of short keyword queries for improving information retrieval from opaque (black box) search engines, according to which data including labeled claims from several fact-checking websites, is collected for creating dataset which is used for evaluation. The relevance of posts/query results retrieved from a search engine to a given input document, is estimated by calculating the mean relevance error (MRE), based on estimating the minimal distance between words comprising both the retrieved posts and the input document. A subset of claims is labeled for evaluation, by choosing a number of claims that gained the maximal and the minimal mean relevance error (MRE). The most appropriate keywords is found in order to retrieve the maximal number of relevant posts using an opaque search engine, by performing an interactive greedy search for the best word that should be added to the input query, for maximizing the corresponding posts retrieved by the search engine.