54 research outputs found

    How to combine visual features with tags to improve movie recommendation accuracy?

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    Previous works have shown the effectiveness of using stylistic visual features, indicative of the movie style, in content-based movie recommendation. However, they have mainly focused on a particular recommendation scenario, i.e., when a new movie is added to the catalogue and no information is available for that movie (New Item scenario). However, the stylistic visual features can be also used when other sources of information is available (Existing Item scenario). In this work, we address the second scenario and propose a hybrid technique that exploits not only the typical content available for the movies (e.g., tags), but also the stylistic visual content extracted form the movie files and fuse them by applying a fusion method called Canonical Correlation Analysis (CCA). Our experiments on a large catalogue of 13K movies have shown very promising results which indicates a considerable improvement of the recommendation quality by using a proper fusion of the stylistic visual features with other type of features

    Modification of forests by people means only 40% of remaining forests have high ecosystem integrity

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    Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally

    Equitable and effective area‐based conservation: towards the conserved areas paradigm

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    In 2018, the Parties to the Convention on Biological Diversity (CBD) adopted a decision on protected areas and other effective area-based conservation measures (OECMs). It contains the definition of an OECM and related scientific and technical advice that has broadened the scope of governance authorities and areas that can be engaged and recognised in global conservation efforts. The voluntary guidance on OECMs and protected areas, also included in the decision, promotes the use of diverse, effective and equitable governance models, the integration of protected areas and OECMs into wider landscapes and seascapes, and mainstreaming of biodiversity conservation across sectors. Taken as a whole, the advice and voluntary guidance provides further clarity about the CBD Parties’ understanding of what constitutes equitable and effective area-based conservation measures within and beyond protected areas and provides standardised criteria with which to measure and report areas’ attributes and performance. This policy perspective suggests that this CBD decision represents further evidence of the evolution from the ‘new paradigm for protected areas’ to a broader ‘conserved areas paradigm’ that embodies good governance, equity and effective conservation outcomes and is inclusive of a diversity of contributions to conservation within and beyond protected areas

    Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity

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    Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remain poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate a globally consistent, continuous index of forest condition as determined by the degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) has high landscape-level integrity (mostly found in Canada, Russia, the Amazon, Central Africa, and New Guinea) and only 27% of this area is found in nationally designated protected areas. Of the forest inside protected areas, only 56% has high landscape-level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally

    Improving Social Filtering Techniques through WordNet-based User Profiles

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    Collaborative filtering algorithms predict the preferences of a user for an item by weighting the contributions of similar users, called neighbors, for that item. Similarity between users is computed by comparing their rating styles, i.e. the set of ratings given on the same items. Unfortunately, similarity between users is computable only if they have common rated items. The main contribution of this paper is a (content-collaborative) hybrid recommender system which overcomes this limitation by computing similarity between users on the ground of their content-based profiles. Traditional keyword-based profiles are unable to capture the semantics of user interests, due to the natural language ambiguity. A distinctive feature of the proposed technique is that a statistical model of the user interests is obtained by machine learning techniques integrated with linguistic knowledge contained in the WordNet lexical database. This model, called the semantic user profile, is exploited by the hybrid recommender in the neighborhood formation process. The results of an experimental session in a movie recommendation scenario demonstrate the effectiveness of the proposed approach
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