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This paper explores a novel application of textual semantic similarity to user-preference representation for rating prediction. The approach represents a user's preferences as a graph of textual snippets from review text, where the edges are defined by sem ...
New York2023
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With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent ...
The presentation is focused on a visual method that allows for a hexagonal arrangement in network visualization. Hexagonal tilling is a way to enrich the betweenness of nodes in order to enrich the information that a network visualization can convey. What ...
This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine ...
We present semantic attribute matching networks (SAM-Net) for jointly establishing correspondences and transferring attributes across semantically similar images, which intelligently weaves the advantages of the two tasks while overcoming their limitations ...
In the present information era, a huge amount of machine-readable data is available regarding scientific publications. Such unprecedented wealth of data offers the opportunity to investigate science itself as a complex interacting system by means of quanti ...
This paper introduces a query refinement method applied to questions asked by users to a system during a meeting or a conversation that they have with other users. To answer the questions, the proposed method leverages the local context of the conversation ...
Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information, such as scene context, semantic relationships, gaze direction, and object dissimilarity. However, none of these models consider t ...
Keyphrase extraction is the task of automatically selecting a small set of phrases that best describe a given free text document. Keyphrases can be used for indexing, searching, aggregating and summarizing text documents, serving many automatic as well as ...
In this letter, we present a semantic mapping approach with multiple hypothesis tracking for data association. As semantic information has the potential to overcome ambiguity in measurements and place recognition, it forms an eminent modality for autonomou ...
