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Journal of Intelligent Information Systems OnlineFirst articles

19.03.2024 | Research

Knowledge-aware adaptive graph network for commonsense question answering

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 …

verfasst von:
Long Kang, Xiaoge Li, Xiaochun An

Open Access 16.03.2024 | Research

A motif-based probabilistic approach for community detection in complex networks

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 …

verfasst von:
Hossein Hajibabaei, Vahid Seydi, Abbas Koochari

15.03.2024 | Research

A hybrid recognition framework of crucial seed spreaders in complex networks with neighborhood overlap

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 …

verfasst von:
Tianchi Tong, Min Wang, Wenying Yuan, Qian Dong, Jinsheng Sun, Yuan Jiang

15.03.2024 | Research

Early detection of fake news on emerging topics through weak supervision

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 …

verfasst von:
Serhat Hakki Akdag, Nihan Kesim Cicekli

02.03.2024 | Research

Ensemble of temporal Transformers for financial time series

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 …

verfasst von:
Kenniy Olorunnimbe, Herna Viktor

29.02.2024 | Research

Enhancing sentiment and emotion translation of review text through MLM knowledge integration in NMT

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 …

verfasst von:
Divya Kumari, Asif Ekbal

20.02.2024 | Research

CMC-MMR: multi-modal recommendation model with cross-modal correction

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 …

verfasst von:
YuBin Wang, HongBin Xia, Yuan Liu

15.02.2024 | Research

Querying knowledge graphs through positive and negative examples and feedback

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 …

verfasst von:
Akritas Akritidis, Yannis Tzitzikas

02.02.2024 | Research

Semantic-enhanced reasoning question answering over temporal knowledge graphs

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 …

verfasst von:
Chenyang Du, Xiaoge Li, Zhongyang Li

25.01.2024 | Research

KIMedQA: towards building knowledge-enhanced medical QA models

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 …

verfasst von:
Aizan Zafar, Sovan Kumar Sahoo, Deeksha Varshney, Amitava Das, Asif Ekbal

Open Access 23.01.2024 | Research

Data- & compute-efficient deviance mining via active learning and fast ensembles

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

22.01.2024 | Research

A novel technique using graph neural networks and relevance scoring to improve the performance of knowledge graph-based question answering systems

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 …

verfasst von:
Sincy V. Thambi, P. C. Reghu Raj

Open Access 19.01.2024 | Research

A qualitative analysis of knowledge graphs in recommendation scenarios through semantics-aware autoencoders

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

19.01.2024 | Research

Sentiment analysis of twitter data to detect and predict political leniency using natural language processing

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

06.01.2024 | Research

Enhancing the fairness of offensive memes detection models by mitigating unintended political bias

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

06.01.2024 | Research

Movie tag prediction: An extreme multi-label multi-modal transformer-based solution with explanation

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

28.12.2023 | Research

TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments

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

26.12.2023 | Research

A bayesian-neural-networks framework for scaling posterior distributions over different-curation datasets

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 …

verfasst von:
Alfredo Cuzzocrea, Alessandro Baldo, Edoardo Fadda

12.12.2023 | Research

Audio super-resolution via vision transformer

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.

verfasst von:
Simona Nisticò, Luigi Palopoli, Adele Pia Romano

12.12.2023 | Research

Tell me what you Like: introducing natural language preference elicitation strategies in a virtual assistant for the movie domain

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