{"title":"Orientation Invariant Tensor Completion In Both Spectual And Space Domains","authors":"Xiangrui Li, Andong Wang, Xiyuan Hu, Zhenmin Tang","doi":"10.1109/WI-IAT55865.2022.00135","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00135","url":null,"abstract":"The performance of most tensor completion algorithms heavily relies on the definition of tensor low-rankness. Among the various low-rank regularizations proposed in the last decade, the Tubal+Tucker Nuclear Norm (T2NN) firstly considers the low rankness both in spectral and space domains. However, this norm is unfortunately sensitive to the orientation, and thus fails to model low-rankness in multiple orientations. To this point, a new tensor norm, dubbed Orientation Invariant Hybrid Nuclear Norm (OIHNN), is first defined and then applied to formulate a new tensor completion model. To solve the model, an efficient algorithm is developed within the framework of Alternating Direction Method of Multipliers (ADMM). Effectiveness of our method is validated through experimental results on real datasets.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121836858","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":"Chinese Painting Algorithm: A Study of Scene Characterization by Chromatographic Multiple Analysis and Handwriting Co-construction","authors":"Ziyang Weng, W. Yan, Y. Hu, Zhimo Weng","doi":"10.1109/WI-IAT55865.2022.00143","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00143","url":null,"abstract":"The understanding of scene representation is a deep knowledge service structure strategy arising from the increasing scale of data and the need for complex logic solving. This study proposes a modeling improvement method based on the fusion of complex feature data and exploration behavior trajectory extremes, which effectively utilizes the artistic feature study of the interplay between the unique colorant mixture attachment features of Chinese painting and complex handwriting features as the orientation region, realizes the classification constraint of colorant data through multispectral detection, and characterizes the handwriting as the behavior law, realizes the parametric extraction and then couples the solution encoding to complete the improvement of the algorithm. Since all scenes in Chinese painting are recorded in the bearer medium with handwriting characteristics after mixing Chinese brushes and colorants, the computational model of Chinese painting algorithm proposed in this paper starts from the processing of representation hierarchical structure and painting behavior of various scenes deposited to realize the principle of describing their material deposition goals and information exchange functions. The experimental analysis shows that i. deep knowledge understanding achieves the derivation of sparse feature validity, ii. the coverage calculation obtained by drawing on technological means can vividly describe the implicit characteristics of handwriting behavior, and iii. the improved modeling process has more humanized perceptual habits and enhances the accuracy and robustness of service domain requirements.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125553172","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":"A Knowledge Graph Construction Method for Food Nutrition","authors":"Libing Qiao, Haisheng Li, Wei Wang, Di Wang","doi":"10.1109/WI-IAT55865.2022.00091","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00091","url":null,"abstract":"Food provides indispensable nutrition to sustain people's life activities. Lack of awareness of the nutritional ingredients in food will lead to health issues caused by an unbalanced diet, inadequate nutrition, and nutritional overload. With more and more sugar-free, low-fat products coming onto the market today, there is a growing concern about the nutritional ingredients of foods. In this paper, we propose the knowledge graph of the nutrition ingredient of food constructed by the hybrid model, which helps users to understand the detailed information of nutrient ingredients more clearly. We first pre-process the data according to the type of data crawled. As for structured data, we convert them into triples, which are used to construct the graph. And as for unstructured data, knowledge extraction technology is mainly used. Knowledge extraction mainly focuses on dependency parsing for relation extraction and performs knowledge fusion on the extracted data to calculate the similarity between data points of different categories. Then, we divide the data of different levels into tree clustering structures to find the lowest cost clustering scheme. Finally, the processed data is stored in the Neo4j graphical database for the visual display of the graph, which helps individuals to understand the nutritional ingredients of food more intuitively.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126135228","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":"Predicting Hateful Discussions on Reddit using Graph Transformer Networks and Communal Context","authors":"Liam Hebert, Lukasz Golab, R. Cohen","doi":"10.1109/WI-IAT55865.2022.00012","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00012","url":null,"abstract":"We propose a system to predict harmful discussions on social media platforms. Our solution uses contextual deep language models and proposes the novel idea of integrating state-of-the-art Graph Transformer Networks to analyze all conversations that follow an initial post. This framework also supports adapting to future comments as the conversation unfolds. In addition, we study whether a community-specific analysis of hate speech leads to more effective detection of hateful discussions. We evaluate our approach on 333,487 Reddit discussions from various communities. We find that community-specific modeling improves performance two-fold and that models which capture wider-discussion context improve accuracy by 28% (35% for the most hateful content) compared to limited context models.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121789507","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":"A Noise-enhanced Fuse Model for Passage Ranking","authors":"Yizheng Huang","doi":"10.1109/WI-IAT55865.2022.00118","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00118","url":null,"abstract":"Since the rapid progress in deep learning in recent years, many language models have achieved significant results in various information retrieval (IR) tasks. Passage ranking plays a vital role in this field, and the neural network models significantly outperform the traditional method. However, fine-tuning the pre-trained model to the downstream task may be influenced by the fact that there are differences between the two tasks. And traditional methods also have their advantages. In some cases, the performance of BM25 is obviously better than the deep learning model. This paper discusses the results of the deep learning model linearly combining with BM25 and adds noise to the model for enhancing the finetune performance. We conduct experiments on the MS MARCO dataset to show convincing results.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121930300","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":"A deep skin cancer classification approach using image and structured information","authors":"Supamdeep Singh, Jiashu Jessie Zhao","doi":"10.1109/WI-IAT55865.2022.00150","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00150","url":null,"abstract":"In this paper we describe an approach to implement a hybrid skin cancer detection machine learning model that uses the combination of two models. The final concatenated model makes prediction based on the information it gains from the two models. The first model being the Convolutional Neural Network model that learns from the image’s dataset and the second Artificial Neural Network model that learns from the textual data associated with the images. Hence the final concatenated model uses these models to make predictions.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122285812","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}
Futoshi Ohyama, Satoshi Iwamoto, Osamu Kita, Takahide Kanatake, Daisuke Yasui, H. Matsumoto, A. Subekti
{"title":"Study on application of communication in JS8 mode in the amateur radio high frequency band for telemedicine in the event of a major disaster","authors":"Futoshi Ohyama, Satoshi Iwamoto, Osamu Kita, Takahide Kanatake, Daisuke Yasui, H. Matsumoto, A. Subekti","doi":"10.1109/wi-iat55865.2022.00111","DOIUrl":"https://doi.org/10.1109/wi-iat55865.2022.00111","url":null,"abstract":"This study examined the possibility of using a new digital mode, JS8 data transmission method on the 7 MHz band of amateur radio, for telemedicine in the event of a major disaster. JS8 mode allows free exchange of text data simply by installing dedicated software on a PC and connecting it to a commercially available amateur radio. We have been experimenting with this communication method for about a year to see how it could be used in disaster medicine. As a result, we have found that this mode of communication can be used even with poor HF(high-frequency) band communication facilities and in a harsh signal-to-noise environment. Although the data transmission rate is as low as 6.25 bps, the results suggest that it can be applied to telemedicine during disasters if the information to be transmitted is carefully examined.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127729626","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":"Morphologically-Aware Vocabulary Reduction of Word Embeddings","authors":"Chong Cher Chia, Maksim Tkachenko, Hady W. Lauw","doi":"10.1109/WI-IAT55865.2022.00018","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00018","url":null,"abstract":"We propose SubText, a compression mechanism via vocabulary reduction. The crux is to judiciously select a subset of word embeddings which support the reconstruction of the remaining word embeddings based on their form alone. The proposed algorithm considers the preservation of the original embeddings, as well as a word’s relationship to other words that are morphologically or semantically similar. Comprehensive evaluation of the compressed vocabulary reveals SubText’s efficacy on diverse tasks over traditional vocabulary reduction techniques, as validated on English, as well as a collection of inflected languages.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129062797","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. Cremaschi, Jessica Amianto Barbato, A. Rula, M. Palmonari, R. Actis-Grosso
{"title":"What Really Matters in a Table? Insights from a User Study","authors":"M. Cremaschi, Jessica Amianto Barbato, A. Rula, M. Palmonari, R. Actis-Grosso","doi":"10.1109/WI-IAT55865.2022.00045","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00045","url":null,"abstract":"Better understanding human visual attention during reading can provide valuable insights for developing user-centred computations models. A considerable amount of data, presented in a tabular form, is used in daily activities and is available on the Web nowadays. Several approaches have proposed an automated table summarisation method to improve the users’ experience and give them succinct summaries of tables. However, there has been little attention to considering user behaviour in the design of automated table summarisation. In this paper, we present the findings of an empirical study, where we investigate, with the help of standard User Experience tools (eye-tracking technology and surveys), how users approach the reading of a table. We focus on evaluating how the domain knowledge and interest of the users influence their comprehension, eventually identifying four possible user-profiles and their different information needs. In order to show the impact of our findings on the selection of the information to keep in summary, we present and release a tool that, in addition to supporting the development of similar experiments, allows checking the information presented in summary in the form of Resource Description Framework (RDF) triples, by exploiting the semantic annotation of the table.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124335683","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":"A Study on Agent Expression and User Gaze Behavior in Product Endorsement Videos","authors":"Chisa Kondo, H. Sakuma, Y. Hijikata","doi":"10.1109/WI-IAT55865.2022.00104","DOIUrl":"https://doi.org/10.1109/WI-IAT55865.2022.00104","url":null,"abstract":"Influencers on social networking and social media share their experiences of using products and services through their own content. This sometimes influences the consumption behavior of their followers. Influencers are increasingly introducing products in video media, and some are being asked by companies to introduce their products. In addition, the appearance of influencers is becoming more diverse, and we believe that the amount of information received by users varies depending on differences in agent representation. Therefore, this study examines whether differences in agent representation in product endorsement videos have different influences on advertising effectiveness (purchase intention after viewing the video, understanding of the product, and attitude toward brand) and viewers’ eye movements. Participants watched one of the following videos: one with a human, one with an avatar, and one with an image of a default icon. The participants then answered a questionnaire. The results of the experiment showed that there was no difference in advertising effectiveness among the three types of agent representations, but there were differences in the likability, and trustworthiness of the agents. And, there was a difference in the physical attraction of the agents between human and avatar. In addition, it was found that the participants’ gaze during video viewing differed between the human video and avatar video.","PeriodicalId":345445,"journal":{"name":"2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124566838","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}