Commonsense Question Answering (CQA) aims to select the correct answers to common knowledge questions. Most existing approaches focus on integrating external knowledge graph (KG) representations with question context representations to facilitate …
Community detection in complex networks is an important task for discovering hidden information in network analysis. Neighborhood density between nodes is one of the fundamental indicators of community presence in the network. A community with a …
Recognizing crucial seed spreaders of complex networks is an open issue that studies the dynamic spreading process and analyzes the performance of networks. However, most of the findings design the hierarchical model based on nodes’ degree such as …
In this paper, we present a methodology for the early detection of fake news on emerging topics through the innovative application of weak supervision. Traditional techniques for fake news detection often rely on fact-checkers or supervised …
The accuracy of price forecasts is important for financial market trading strategies and portfolio management. Compared to traditional models such as ARIMA and other state-of-the-art deep learning techniques, temporal Transformers with similarity …
Producing a high-quality review translation is a multifaceted process. It goes beyond successful semantic transfer and requires conveying the original message’s tone and style in a way that resonates with the target audience, whether they are …
Multi-modal recommendation using multi-modal features (e.g., image and text features) has received significant attention and has been shown to have more effective recommendation. However, there are currently the following problems with multi-modal …
The formulation of structured queries over Knowledge Graphs is not an easy task. To alleviate this problem, we propose a novel interactive method for SPARQL query formulation, for enabling users (plain and advanced) to formulate gradually queries …
Question Answering Over Temporal Knowledge Graphs (TKGQA) is an important topic in question answering. TKGQA focuses on accurately understanding questions involving temporal constraints and retrieving accurate answers from knowledge graphs. In …
Medical question-answering systems require the ability to extract accurate, concise, and comprehensive answers. They will better comprehend the complex text and produce helpful answers if they can reason on the explicit constraints described in …
Detecting deviant traces in business process logs is crucial for modern organizations, given the harmful impact of deviant behaviours (e.g., attacks or faults). However, training a Deviance Prediction Model (DPM) by solely using supervised …
verfasst von:
Francesco Folino, Gianluigi Folino, Massimo Guarascio, Luigi Pontieri
A Knowledge Graph-based Question Answering (KGQA) system attempts to answer a given natural language question using a knowledge graph (KG) rather than from text data. The current KGQA methods attempt to determine whether there is an explicit …
Knowledge Graphs (KGs) have already proven their strength as a source of high-quality information for different tasks such as data integration, search, text summarization, and personalization. Another prominent research field that has been …
verfasst von:
Vito Bellini, Eugenio Di Sciascio, Francesco Maria Donini, Claudio Pomo, Azzurra Ragone, Angelo Schiavone
This paper analyses Twitter data to detect the political lean of a profile by extracting and classifying sentiments expressed through tweets. The work utilizes natural language processing, augmented with sentiment analysis algorithms and machine …
verfasst von:
V. V. Sai Kowsik, L. Yashwanth, Srivatsan Harish, A. Kishore, Renji S, Arun Cyril Jose, Dhanyamol M V
This paper tackles the critical challenge of detecting and mitigating unintended political bias in offensive meme detection. Political memes are a powerful tool that can be used to influence public opinion and disrupt voters’ mindsets. However …
verfasst von:
Gitanjali Kumari, Anubhav Sinha, Asif Ekbal, Arindam Chatterjee, Vinutha B N
Providing rich and accurate metadata for indexing media content is a crucial problem for all the companies offering streaming entertainment services. These metadata are commonly employed to enhance search engine results and feed recommendation …
verfasst von:
Massimo Guarascio, Marco Minici, Francesco Sergio Pisani, Erika De Francesco, Pasquale Lambardi
Retail companies are greatly interested in performing continuous monitoring of purchase traces of customers, to identify weak customers and take the necessary actions to improve customer satisfaction and ensure their revenues remain unaffected. In …
verfasst von:
Vincenzo Pasquadibisceglie, Annalisa Appice, Giuseppe Ieva, Donato Malerba
In this paper, we propose and experimentally assess an innovative framework for scaling posterior distributions over different-curation datasets, based on Bayesian-Neural-Networks (BNN). Another innovation of our proposed study consists in …
Audio super-resolution refers to techniques that improve the audio signals quality, usually by exploiting bandwidth extension methods, whereby audio enhancement is obtained by expanding the phase and the spectrogram of the input audio traces.
Preference elicitation is a crucial step for every recommendation algorithm. In this paper, we present a strategy that allows users to express their preferences and needs through natural language statements. In particular, our natural language …
verfasst von:
Cataldo Musto, Alessandro Francesco Maria Martina, Andrea Iovine, Fedelucio Narducci, Marco de Gemmis, Giovanni Semeraro