Blar i NTNU Open på forfatter "Ramampiaro, Heri"
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A deep network model for paraphrase detection in short text messages
Agarwal, Basant; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano (Journal article; Peer reviewed, 2018)This paper is concerned with paraphrase detection, i.e., identifying sentences that are semantically identical. The ability to detect similar sentences written in natural language is crucial for several applications, such ... -
A Hybrid Multi-document Summarization System for Biomedical Articles
Stang, Helene Janine; Sollid, Ingeborg Sætersdal (Master thesis, 2021)Hovedmålet med dette arbeidet er å undersøke hvordan tekstsammendrag kan brukes til å støtte beslutningsprosesser i det biomedisinske domenet, spesielt for diagnostisering cerebral parese. Maskinlæring har vist et stort ... -
A Hybrid Multi-document Summarization System for Biomedical Articles
Stang, Helene Janine; Sollid, Ingeborg Sætersdal (Master thesis, 2021)Hovedmålet med dette arbeidet er å undersøke hvordan tekstsammendrag kan brukes til å støtte beslutningsprosesser i det biomedisinske domenet, spesielt for diagnostisering cerebral parese. Maskinlæring har vist et stort ... -
Anomaly Detection in Infant Movement for Predicting Cerebral Palsy
Løkensgard, Håvard; Skarpnes, Erlend Johann (Master thesis, 2020)Cerebral parese er en permanent motorisk dysfunksjon uten en eksisterende kur. Selv om det ikke er noen etablerte tester for å oppdage dens tilstedeværelse, kan tidlig diagnose og behandling i stor grad forbedre sjansene ... -
Anomaly Detection in Infant Movement for Predicting Cerebral Palsy
Løkensgard, Håvard; Skarpnes, Erlend Johann (Master thesis, 2020)Cerebral parese er en permanent motorisk dysfunksjon uten en eksisterende kur. Selv om det ikke er noen etablerte tester for å oppdage dens tilstedeværelse, kan tidlig diagnose og behandling i stor grad forbedre sjansene ... -
Applying temporal dependence to detect changes in streaming data
Duong, Quang-Huy; Ramampiaro, Heri; Nørvåg, Kjetil (Journal article; Peer reviewed, 2018)Detection of changes in streaming data is an important mining task, with a wide range of real-life ap- plications. Numerous algorithms have been proposed to efficiently detect changes in streaming data. However, the ... -
Bayesian Text Categorization
Næss, Arild Brandrud (Master thesis, 2007)Natural language processing is an interdisciplinary field of research which studies the problems and possibilities of automated generation and understanding of natural human languages. Text categorization is a central ... -
Convolutional networks for video-based infant movement analysis. Towards objective prognosis of cerebral palsy from infant spontaneous movements
Groos, Daniel (Doctoral theses at NTNU;2022:191, Doctoral thesis, 2022)Norsk sammendrag Cerebral parese (CP) er en samlebetegnelse på motoriske funksjonsforstyrrelser grunnet skade på hjernen tidlig i barnets utvikling. Det er særlig spedbarn med medisinske risikofaktorer, som for eksempel ... -
Deep Contextual Grid Triplet Network for Context-Aware Recommendation
Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano (Peer reviewed; Journal article, 2023)Modeling contextual information is a vital part of developing effective recommender systems. Still, existing work on recommendation algorithms has generally put limited focus on the effective treatment of contextual ... -
Density Guarantee on Finding Multiple Subgraphs and Subtensors
Duong, Quang-Huy; Ramampiaro, Heri; Nørvåg, Kjetil (Peer reviewed; Journal article, 2021)Dense subregion (subgraph & subtensor) detection is a well-studied area, with a wide range of applications, and numerous efficient approaches and algorithms have been proposed. Approximation approaches are commonly used ... -
Detecting and Grading Hateful Messages in the Norwegian Language
Andreassen Svanes, Marie; Seim Gunstad, Tora (Master thesis, 2020)I dagens samfunn har det blitt stadig enklere å uttrykke sin mening gjennom utstrakt bruk av sosiale media og diskusjonsfora. Det har også blitt vanskeligere å forebygge nettmobbing og opprettholde trygghet på Internett ... -
Detecting and Grading Hateful Messages in the Norwegian Language
Svanes, Marie Andreassen; Gunstad, Tora Seim (Master thesis, 2020)I dagens samfunn har det blitt stadig enklere å uttrykke sin mening gjennom utstrakt bruk av sosiale media og diskusjonsfora. Det har også blitt vanskeligere å forebygge nettmobbing og opprettholde trygghet på Internett ... -
Detecting hateful utterances using an anomaly detection approach
Jensen, Maria Hilmo (Master thesis, 2020)Forskning på sikkerhet i sosiale medier har vokst betydelig det siste tiåret. Med den utbredte bruken av nettbaserte tjenester og sosiale medier, har det blitt enkelt å spre hatefulle meldinger. Selv om ytringsfrihet anses ... -
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches
Tiwari, Shweta; Bell, Gavin; Langseth, Helge; Ramampiaro, Heri (Peer reviewed; Journal article, 2022)Detecting potential manipulations by monitoring trading activities in the electricity market is a time- consuming and challenging task despite the involvement of experienced market surveillance experts. This is due to the ... -
Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk
Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Boswell, Lynn; De Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-Spira, Deborah; Haukeland, Andreas; Loennecken, Marianne; Msall, Michael; Moinichen, Unn Inger; Pascal, Aurelie; Peyton, Colleen; Ramampiaro, Heri; Schreiber, Michael D.; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Thomas, Niranjan; van den Broeck, Christine; Øberg, Gunn Kristin; Ihlen, Espen Alexander F.; Støen, Ragnhild (Peer reviewed; Journal article, 2022)Importance Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity. Objective ... -
Effective hate-speech detection in Twitter data using recurrent neural networks
Pitsilis, Georgios; Ramampiaro, Heri; Langseth, Helge (Journal article; Peer reviewed, 2018)This paper addresses the important problem of discerning hateful content in social media. We propose a detection scheme that is an ensemble of Recurrent Neural Network (RNN) classifiers, and it incorporates various features ... -
Evaluating Top-N Recommendations Using Ranked Error Approach: An Empirical Analysis
Aftab, Sofia; Ramampiaro, Heri (Peer reviewed; Journal article, 2022)Evaluation metrics or measures are necessary tools for evaluating and choosing the most appropriate modeling approaches within recommender systems. However, evaluation measures can sometimes fall short when evaluating ... -
Event Detection in Changing and Evolving Environments
Duong, Huy Quang (Doctoral theses at NTNU;2021:61, Doctoral thesis, 2021)The availability of modern technology and the recent proliferation of devices and sensors have resulted in a tremendous amount of data being generated, stored and handled in various applications that affect almost all ... -
Explaining deep learning methods for recommender systems
Bjørgen, Erik; Hambro, Carl Johan (Master thesis, 2019)Systemkrav for anbefalingssystemer er i stadig endring. Formatet til anbefalinger, samt GDPR, har bragt med seg nye krav for anbefalingene som blir gitt. Forklarbarhet eller tolkbarhet er ett av disse nye kravene. orklarbarhet ... -
Explaining deep learning methods for recommender systems
Bjørgen, Erik; Hambro, Carl Johan (Master thesis, 2019)Systemkrav for anbefalingssystemer er i stadig endring. Formatet til anbefalinger, samt GDPR, har bragt med seg nye krav for anbefalingene som blir gitt. Forklarbarhet eller tolkbarhet er ett av disse nye kravene. Forklarbarhet ...