{"title":"Using Deep Learning to Detect Islamophobia on Reddit","authors":"Esraa Aldreabi, Justin Lee, Jeremy Blackburn","doi":"10.32473/flairs.36.133324","DOIUrl":"https://doi.org/10.32473/flairs.36.133324","url":null,"abstract":"\u0000 \u0000 \u0000Islamophobia, a negative predilection towards the Muslim community, is present on social media platforms. In addition to causing harm to victims, it also hurts the reputation of social media platforms that claim to provide a safe online environment for all users. The volume of social media content is impossible to be manually reviewed, thus, it is important to find automated solutions to combat hate speech on social media platforms. Machine learning approaches have been used in the literature as a way to automate hate speech detection. In this paper, we use deep learning techniques to detect Islamophobia over Reddit and topic modeling to analyze the content and reveal topics from comments identified as Islamophobic. Some topics we identified include the Islamic dress code, religious practices, marriage, and politics. To detect Islamophobia, we used deep learning models. The highest performance was achieved with BERTbase+CNN, with an F1-Score of 0.92. \u0000 \u0000 \u0000","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129086364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple View Summarization Framework for Social Media","authors":"Alen Chih-Yuan Li, S. Chun, J. Geller","doi":"10.32473/flairs.36.133169","DOIUrl":"https://doi.org/10.32473/flairs.36.133169","url":null,"abstract":"Social Media provide voluminous posts about current topics and events. When a user desires to investigate a popular topic, it is not feasible as there are many posts. Besides, posts show different biases, viewpoints, perspectives, and emotions. Thus, providing summaries of large post sets with different viewpoints is necessary. We develop a multiple view summa-rization framework to generate different view-based summar-ies of Twitter posts. Users can apply different methods to generate summaries: 1) Entity-centered, 2) Social feature-based, 3) Event-based summarization, using all triple embed-dings and 4) Sentiment-based summarization to generate summaries of positive or negative views of tweets. These summarization methods are compared with BertSum, SBert, T5, and Bart-Large-CNN with a gold standard dataset. Our results, based on Rouge scores, were better than these pub-lished extractive and abstractive summarization models.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129111463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Rajesh, Sanjiv Sridhar, C. Kulkarni, Aaditya Shah, N. S
{"title":"Weight-based multi-stream model for Multi-Modal Video Question Answering","authors":"M. Rajesh, Sanjiv Sridhar, C. Kulkarni, Aaditya Shah, N. S","doi":"10.32473/flairs.36.133306","DOIUrl":"https://doi.org/10.32473/flairs.36.133306","url":null,"abstract":"There has been a tremendous success in individual domains of Computer Vision, Natural Language Processing, and Knowledge Representation. Videos are a rich source of information with the multi-modal data forms of images, audio, and optionally subtitles blended. Current research is going on in combining these individual domains which have given rise to topics such as image captioning, visual question answering, and video question answering. Video Question Answering is a model which combines research topics like object detection and recognition, temporal information processing, visual attention, and natural language processing. In this paper, we propose a model with Attention Mechanism for Video Question Answering that assigns varying weights to the many pieces of information the video encompasses. The model combines the question with 3 streams i.e., video's frames, subtitles, and objects to get the most probable answer. The model also receives the set of answer candidates as input and predicts one of them as the most probable answer since it has been trained and tested on the TVQA dataset.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126984745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simon Schiff, Mena Leemhuis, Ö. Özçep, Ralf Möller
{"title":"Query Transformation for Processing Streams in Decision-making Agents","authors":"Simon Schiff, Mena Leemhuis, Ö. Özçep, Ralf Möller","doi":"10.32473/flairs.36.133104","DOIUrl":"https://doi.org/10.32473/flairs.36.133104","url":null,"abstract":"An agent in pursuit of a task repeatedly perceives its environment through sensors, updates its state based on observations, and then decides which action to take, given the current state of the environment. Observations have in common that they are made at a given time point and thus referred to as temporal data. Usually, such temporal data is provided as stream data if the agent continuously receives the data, or it is provided as historic data if the stream data is stored in, for instance, a database the agent has access to. DBMSs are especially designed to process static data (i.e. non-temporal data) given a declarative query language such as SQL. However, if the aim is to exploit temporal data as required in time series analysis, SQL has its limits because it does not provide useful abstractions such as a window operator. Hence high-level declarative stream query languages, equipped with time-based window operators were designed. A challenge of those abstractions is the additional overhead of the algorithms that automatically transform high-level queries into low-level queries executable over DBMSs. If not handled properly those transformation algorithms may result in low-level queries with processing times too long for agents to make decisions. We describe a robust and optimized transformation algorithm for a high-level declarative stream query language and show that it leads to low-level queries with feasible processing times on real-world data.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130411353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of Techniques for Sim2Real Reinforcement Learning","authors":"Mahesh Ranaweera, Q. Mahmoud","doi":"10.32473/flairs.36.133317","DOIUrl":"https://doi.org/10.32473/flairs.36.133317","url":null,"abstract":"Reinforcement learning (RL) has demonstrated promising results in transferring learned policies from simulation to real-world environments. However, inconsistencies and discrepancies between the two environments cause a negative transfer. The phenomenon is commonly known as the “reality gap.” The reality gap prevents learned policies from generalizing to the physical environment. This paper aims to evaluate techniques to improve sim2real learning and bridge the reality gap using RL. For this research, a 3-DOF Stewart Platform was built virtually and physically. The goal of the platform was to guide and balance the marble towards the center of the Stewart platform. Custom API was created to induce noise, manipulate in-game physics, dynamics, and lighting conditions, and perform domain randomization to improve generalization. Two RL algorithms; Q-Learning and Actor-Critic were implemented to train the agent and to evaluate the performance in bridging the reality gap. This paper outlines the techniques utilized to create noise, domain randomization, perform training, results, and observations. Overall, the obtained results show the effectiveness of domain randomization and inducing noise during the agents' learning process. Additionally, the findings provide valuable insights into implementing sim2real RL algorithms to bridge the reality gap.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"396 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121795427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recognition of Object Presence and Material Type in a Water Container Using High Frequency Ultrasound","authors":"Mehul Vishal Sadh, Manfred Huber","doi":"10.32473/flairs.36.133313","DOIUrl":"https://doi.org/10.32473/flairs.36.133313","url":null,"abstract":"Detection and characterization of soluble, diffuse, and solid objects and their characteristics in water has important implications in various applications, including water quality assessment and incontinence monitoring for health applications. In particular in the latter task, it is essential to be able to non-intrusively detect the appearance, presence, and consistency of materials in the water without the need for special purpose instruments or a special purpose setting. To achieve this, this work investigates the potential use of high frequency sonar sensors retrofitted to an existing, water-filled container to detect and characterize events where materials are added to the water, and to classify characteristics of the materials in terms of solubility, granularity, and density.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126211717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Leveraging Demonstrations for Learning the Structure and Parameters of Hierarchical Task Networks","authors":"Philippe Hérail, Arthur Bit-Monnot","doi":"10.32473/flairs.36.133327","DOIUrl":"https://doi.org/10.32473/flairs.36.133327","url":null,"abstract":"\u0000Hierarchical Task Networks (HTNs) are a common formalism for automated planning, allowing to leverage the hierarchical structure of many activities. \u0000While HTNs have been used in many practical applications, building a complete and efficient HTN model remains a difficult and mostly manual task. \u0000 \u0000In this paper, we present an algorithm for learning such hierarchical models from a set of demonstrations. \u0000Given an initial vocabulary of tasks and accompanying demonstrations of possible ways to achieve them, we present how each task can be associated with a set of methods capturing the knowledge of how to achieve it. \u0000We focus on the algorithms used to learn the structure of the model and to efficiently parameterize it, as well as an evaluation in terms of planning performance. \u0000","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129849007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic FastMap: An Efficient Algorithm for Spatiotemporal Embedding of Dynamic Graphs","authors":"Omkar Thakoor, T. K. S. Kumar","doi":"10.32473/flairs.36.133526","DOIUrl":"https://doi.org/10.32473/flairs.36.133526","url":null,"abstract":"Efficiently embedding graphs in a Euclidean space has many benefits: It allows us to interpret and solve graph-theoretic problems using geometric and analytical methods. It also allows us to visualize graphs and support human-in-the-loop decision-making systems. FastMap is a near-linear-time graph embedding algorithm that has already found many real-world applications. In this paper, we generalize FastMap to Dynamic FastMap, which efficiently embeds dynamic graphs, i.e., graphs with time-dependent edge-weights, in a spatiotemporal space with a user-specified number of dimensions, while reserving one dimension for representing time. Through a range of experiments, we also demonstrate the efficacy of Dynamic FastMap as an algorithm for spatiotemporal embedding of dynamic graphs.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128328547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Observational Equivalence of Conditional Belief Bases","authors":"C. Beierle, J. Haldimann, Leon Schwarzer","doi":"10.32473/flairs.36.133269","DOIUrl":"https://doi.org/10.32473/flairs.36.133269","url":null,"abstract":"In nonmonotonic reasoning, a conditional of the form ‘If A then usually B’ is typically accepted if a situation where both A and B hold is deemed to be more plausible, more probable, or less surprising, etc., than a situation where A holds, but B does not hold. In a propositional setting, this leads to a relation on the propositional interpretations, also called worlds, by comparing worlds according to their plausibility. In this paper, we address the question of which kind of relations on the set of worlds can be obtained by completing a conditional belief base via an inductive inference operator. As a key concept for our investigations, we introduce and employ the notion of observational equivalence of belief bases that takes an inductive inference operator and a set of queries into account. This leads to the notion of the observational normal form (ONF) and, by focussing on so-called base conditionals, to the base conditional normal form (BCNF). The acceptance of base conditionals corresponds to the plausibility ordering on possible worlds induced by an inference method. Both normal forms ONF and BCNF are combined with renamings as an additional dimension. We establish the interrelationships among the normal forms and evaluate them empirically with respect to systematically generated belief bases.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117299457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Christoforou, Timothy C. Papadopoulos, Maria Theodorou
{"title":"Regularized Neural-Congruency on Spoonerism: Toward exploring the neural-underpinnings of reading disorders on phonological processing tasks","authors":"C. Christoforou, Timothy C. Papadopoulos, Maria Theodorou","doi":"10.32473/flairs.36.133038","DOIUrl":"https://doi.org/10.32473/flairs.36.133038","url":null,"abstract":"Children’s performance on the spoonerism task, a behavioral test that measures phonological processing skills, predicts reading abilities and related disorders. However, this relationship between phonological processing skills and dyslexia has been primarily examined based on behavioral responses to the spoonerism task. As a result, there is a growing interest in developmental neuroscience to explore the neural origins of this relationship and its relation to reading difficulties. Yet, traditional electroencephalography (EEG) analysis methods had little success identifying informative neural components that depict neural differences in children with reading disorders during spoonerism. The current study explores a novel computational approach to isolate informative neural signatures elicited during the spoonerism test. We apply our method to EEG data obtained from a group of children with dyslexia and controls during the execution of a spoonerism task. Our findings demonstrate that our method extracts components that characterize the neural origins of complex cognitive phonological processes, explains differences between children with dyslexia and controls, and generates novel insights into the neural underpinnings of dyslexia in children.","PeriodicalId":302103,"journal":{"name":"The International FLAIRS Conference Proceedings","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124781382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}