Nicolas Torzec

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While some web search users know exactly what they are looking for, others are willing to explore other topics related to an initial interest. Often, the user's initial interest can be uniquely linked to an entity in a knowledge base, and in this case it is natural to recommend the explicitly linked entities for further exploration. In real world knowledge(More)
We propose a model for automatically cropping images based on a diverse set of content and spatial features. We approach this by extracting pixel-level features and aggregating them over possible crop regions. We then learn a regression model to predict the quality of the crop regions, via the degree to which they would overlaps with human-provided crops(More)
Entity ranking is a recent paradigm that refers to retrieving and ranking related objects and entities from different structured sources in various scenarios. Entities typically have associated categories and relationships with other entities. In this work, we present an extensive analysis of Web-scale entity ranking, based on machine learned ranking models(More)
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