8 research outputs found

    RecTwitter: A Rule-Based Semantic Recommender System for Twitter Users

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    Twitter is a microblog that contains large amounts of users who contribute with messages for a wide variety of real-world events. It is possible to identify users who share the same interests using the messages published in their timeline. However, those users can stop publishing interesting content anytime, thus finding any interesting content manually is a hard task. Taken into account users\u27 access on Twitter, he may lose important tweets, or only a part of all tweets will be relevant to him. Indeed, we can observe that it is important to develop automated mechanisms to filter out these messages. In this project, we propose a semantic recommendation system based on SWRL rules to recommend accounts to be followed or unfollowed. To evaluate the recommendations, we conducted an experiment with real users. The results show that 80% of the recommendations were generated to unfollow and 20% to follow some account

    Exploiting Linked Open Data for a Collaborative Filtering Recommendation System

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    Recommendation Systems (RS) tackle Information Overload on the web, and Collaborative Filtering (CF) is a widely used technique to estimate content relevance for users based on similar profiles. Traditional CF, however, often overlooks hidden semantic information and item relationships. This work proposes an RS that integrates Linked Open Data with CF to improve recommendation precision by leveraging semantic information about resources and their relationships. The approach calculates semantic similarity among resources using the Linked Open Data graph. By comparing error rates (MAE and RMSE) in varying scenarios, the proposed approach shows at least a 1.5% improvement in precision rates compared to traditional CF. This study contributes insights for researchers seeking to exploit Linked Open Data in recommendation contexts

    Exploiting Web Features for Relevance Feedback

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    Keyword-search is the prevalent method for finding information on the Web today. However more expressive methods to acknowledge the intriguing characteristics of today’s user/content combination on the Web are required. Based on this premise, this paper sets forth to investigate a very expressive method called relevance feedback, on which the user judges the relevance of pages and continuously redirect the search toward the assumed user-preferred pages. This proposal incorporates relevance feedback into a completely functioning search engine to improve the functioning keyword-searching mechanism. We investigate a number of web page features, which could be pursued for ranking pages according to relevance feedback. By applying supervised learning algorithms, we aim at determining how those features should be weighed for the best outcome in ranking and thus engineered for relevance feedback

    The role of Glu498 in the dioxygen reactivity of CotA-laccase from Bacillus subtilis

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    The multicopper oxidases couple the one-electron oxidation of four substrate molecules to the four electron reductive cleavage of the O-O bond of dioxygen. This reduction takes place at the trinuclear copper centre of the enzyme and the dioxygen approaches this centre through an entrance channel. In this channel, an acidic residue plays a key role in steering the dioxygen to the trinuclear copper site, providing protons for the catalytic reaction and giving overall stability to this site. In this study, the role of the Glu(498) residue, located within the entrance channel to the trinuclear copper centre, has been investigated in the binding and reduction of dioxygen by the CotA-laccase from Bacillus subtilis. The absence of an acidic group at the 498 residue, as in the E498T and E498L mutants, results in a severe catalytic impairment, higher than 99%, for the phenolic and non-phenolic substrates tested. The replacement of this glutamate by aspartate leads to an activity that is around 10% relative to that of the wild-type. Furthermore, while this latter mutant shows a similar K-m value for dioxygen, the E498T and E498L mutants show a decreased affinity, when compared to the wild-type. X-ray structural and spectroscopic analysis (UV-visible, electron paramagnetic resonance and resonance Raman) reveal perturbations of the structural properties of the catalytic centres in the Glu(498) mutants when compared to the wild-type protein. Overall, the results strongly suggest that Glu(498) plays a key role in the protonation events that occur at the trinuclear centre and in its stabilization, controlling therefore the binding of dioxygen and its further reduction