Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics最新文献

{"title":"Evaluation of retweet clustering method classification method using retweets on Twitter without text data","authors":"Kazuki Uchida, F. Toriumi, Takeshi Sakaki","doi":"10.1145/3106426.3106451","DOIUrl":"https://doi.org/10.1145/3106426.3106451","url":null,"abstract":"Burst phenomena, which frequently occur on social media, are caused by such social events as flaming on the internet, elections, and natural disasters. To understand people's thoughts and feelings, we must classify their opinions from burst phenomena. Therefore, classification methods that categorize tweets are critical. However, since most classification methods focus on text mining, they cannot group tweets by topics because each tweet has poor linguistic similarities. We used a non-text-based classification method proposed by Baba et al. that groups tweets by topics, even if they have poor linguistic similarities, and verified its validity by comparing it with a text-based classification method in two different evaluations: qualitative and quantitative. In the qualitative evaluation part, we did a questionnaire survey and validated the suitability of the topic clusters created using both the non-and text-based methods. Since evaluating the similarity of every pair of tweets in each topic is difficult, we evaluated the similarity between sampled pairs in the survey and acquired more appropriate topic clustering results using the non-text-based method than the text-based method. In the quantitative evaluation part, we focused on the robustness of each method against data reduction. Many approaches analyze social media data, especially because collecting data from social media is comparatively easy. However, since collecting the whole data of burst phenomena is very costly due to the vast amounts of available social media data, robustness against data reduction is an important index to evaluate classification methods. With the non-text-based method, over 55% of the pairs of tweets in the same cluster were also included in the same cluster even when the data were reduced to 10% in all three of our example cases. In this paper, as a source we focus on Twitter, one of the most popular microblogging services. Using clustering to conduct detailed case analyses, we scrutinized three burst cases that include natural disasters and flaming on the internet and found that a non-text-based method more effectively classified tweets in burst phenomena than a text-based method.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82997566","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 new urban segregation-growth coupled model using a belief-desire-intention possibilistic framework","authors":"Meili Vanegas-Hernandez, C. Pereira, Diego Moreno, Giovanni Fusco, A. Tettamanzi, M. Riveill, J. T. Hernández","doi":"10.1145/3106426.3106486","DOIUrl":"https://doi.org/10.1145/3106426.3106486","url":null,"abstract":"We study the feasibility of using Belief, Desire and Intention agents for modeling the phenomena of urban growth and segregation. Uncertainty, typical of real world situations is modeled using possibility theory. We have also implemented a simple visualization tool whose aim is to track the changes in the model. Some preliminary experiments suggest that such an approach might allow a decision-maker to dynamically track the changes in the model. Besides, it is also possible to interact with the different steps of the simulation via the model. Our proposal makes it possible to simulate the interactions between cognitive agents in an economical environment while taking the spatial context into account.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89470866","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 path-based model for emotion abstraction on facebook using sentiment analysis and taxonomy knowledge","authors":"Valentina Franzoni, Yuanxi Li, Paolo Mengoni","doi":"10.1145/3106426.3109420","DOIUrl":"https://doi.org/10.1145/3106426.3109420","url":null,"abstract":"Each term in a short text can potentially convey emotional meaning. Facebook comments and shared posts often convey human biases, which play a pivotal role in information spreading and content consumption. Such bias is at the basis of human-generated content, and capable of conveying contexts which shape the opinion of users through the social media flow of information. Starting from the observation that a separation in topic clusters, i.e. sub-contexts, spontaneously occur if evaluated by human common sense, this work introduces a process for automated extraction of sub-context in Facebook. Basing on emotional abstraction and valence, the automated extraction is exploited through a class of path-based semantic similarity measures and sentiment analysis. Experimental results are obtained using validated clustering techniques on such features, on the domain of information security, over a sample of over 9 million page users. An additional expert evaluation of clusters in tag clouds confirms that the proposed automated algorithm for emotional abstraction clusters Facebook comments compatibly with human common sense. The baseline methods rely on the robust notion of collective concept similarity.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86761935","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":"The case for including senior citizens in the playable city","authors":"Julian Fietkau","doi":"10.1145/3106426.3109042","DOIUrl":"https://doi.org/10.1145/3106426.3109042","url":null,"abstract":"The topic of \"playable cities\" has recently emerged as a variation on smart cities, focusing on ways to make urban spaces more playfully interactive and fun by incorporating digital technology. Existing work in this field has largely focused on explorative design and case studies. As of yet, there are barely any design guidelines specific to the context. In this paper, we motivate the need for urban interaction designers to consider the restrictions of senior citizens, give a broad overview over interaction design recommendations for older adults as relevant for urban spaces, examine selected published \"playable city\" case studies for their suitability regarding this population group, and propose some preliminary design guidelines for future work.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88971062","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":"Research and development of domain dictionary construction system","authors":"Yonghong Cheng, Yi Huang","doi":"10.1145/3106426.3109046","DOIUrl":"https://doi.org/10.1145/3106426.3109046","url":null,"abstract":"With the rapid development of science and technology, every day there are a large number of data in various forms produced on the Internet. Domain vocabularies embody the core knowledge of a subject field, and they play important role in parsing, tagging and understanding domain literature, as well as grasping the development of the subject field status with theoretical and practical significance. Currently, most of these dictionaries are constructed manually by domain experts, and there is an urgent need to develop a professional dictionary construction system to facilitate the construction and editing process. This paper investigates the functions of several dictionary systems home and abroad, designs the overall framework and component modules, and builds a dictionary construction system. The implementation and application of the system show that it can effectively support the professional dictionary construction process.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88502054","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":"Development of applications for teaching assistant robots with teachers in PRINTEPS","authors":"Shunsuke Akashiba, Chihiro Nishimoto, Naoya Takahashi, Takeshi Morita, Reiji Kukihara, Misae Kuwayama, Takahira Yamaguchi","doi":"10.1145/3106426.3109412","DOIUrl":"https://doi.org/10.1145/3106426.3109412","url":null,"abstract":"PRINTEPS is currently being developed as a total intelligent application, which has sub systems for knowledge-based reasoning, speech dialogue, image sensing, motion planning, and machine learning, in order to support end users on easily developing intelligent applications for human-machine collaboration. In this paper, a lesson application for collaborative teaching among a robot, laptop PC, sensor, teachers and students was developed with PRINTEPS. The implementation lesson was performed in a science class for six grade elementary students.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91537646","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":"LOG4MEX: a library to export machine learning experiments","authors":"Diego Esteves, Diego Moussallem, Tommaso Soru, C. Baron, Jens Lehmann, A. N. Ngomo, J. C. Duarte","doi":"10.1145/3106426.3106530","DOIUrl":"https://doi.org/10.1145/3106426.3106530","url":null,"abstract":"A choice of the best computational solution for a particular task is increasingly reliant on experimentation. Even though experiments are often described through text, tables, and figures, their descriptions are often incomplete or confusing. Thus, researchers often have to perform lengthy web searches for reproducing and understanding the results. In order to minimize this gap, vocabularies and ontologies have been proposed for representing data mining and machine learning (ML) experiments. However, we still lack proper tools to export properly these metadata. To this end, we present an open-source library dubbed LOG4MEX which aims at supporting the scientific community to fulfill this gap.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85652449","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":"Tie strength dynamics over temporal co-authorship social networks","authors":"Michele A. Brandão, Pedro O. S. Vaz de Melo, Mirella M. Moro","doi":"10.1145/3106426.3106536","DOIUrl":"https://doi.org/10.1145/3106426.3106536","url":null,"abstract":"In co-authorship social networks, nodes are authors linked by co-authorship interactions. As time is a relevant aspect of such interactions, concepts and metrics designed to static networks have to be adapted to temporal networks. Tie strength is one of those concepts. Here, we verify if current tie strength definitions are valid for temporal networks by analyzing the strength of ties dynamism over temporal co-authorship networks. Surprisingly, our results show that most ties, even the strong ones, tend to perish over time. Thus, most co-authorships are symbiotic without positive concerns. Also, real co-authorship social networks from different research areas have more weak and random ties than strong and bridge ties.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"124 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91051728","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":"Multi-goal pathfinding in ubiquitous environments: modeling and exploiting knowledge to satisfy goals","authors":"O. Kem, Flavien Balbo, Antoine Zimmermann","doi":"10.1145/3106426.3109054","DOIUrl":"https://doi.org/10.1145/3106426.3109054","url":null,"abstract":"Multi-goal pathfinding (MGPF) is a problem of searching for a path between a start and a destination allowing a set of goals to be satisfied. We address MGPF in ubiquitous environments that accommodate cyber, physical and social (CPS) entities from smart objects to sensors and to humans. Given a MGPF problem in a pervasive environment, our approach aims at exploiting data from various resources including CPS entities located in the environment and external resources such as the Web to solve the problem. In this paper, we present a knowledge model for describing a ubiquitous environment integrating its spatial dimension, CPS entities it contains and its relevant resources. A global view of the approach is provided. We address particularly one of the challenges in MGPF, namely goal satisfaction problem, which consists of identifying through which entities a goal can be satisfied. Towards this aim, we design an ontology to formally model CPS entities, goals and their relations. We describe a method to exploit modeled knowledge in order to solve the goal satisfaction problem.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89049594","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":"Arabic ontology learning using deep learning","authors":"Saeed Al-Bukhitan, T. Helmy, A. Al-Nazer","doi":"10.1145/3106426.3109052","DOIUrl":"https://doi.org/10.1145/3106426.3109052","url":null,"abstract":"Ontology, the backbone of Semantic Web, is defined as the formal specification of conceptual hierarchy with relationships between concepts. Ontology Learning (OL) is a process to create an ontology from text automatically or semi-automatically. OL is an important topic in the Semantic Web field in the last two decades but it is still not mature in Arabic not like Latin languages. Currently, there is a limited support for using knowledge from Arabic literature automatically in semantically-enabled systems. Deep Learning (DL), an artificial neural networks learning based application, has proved a good improvement in multiple areas including text mining. By using DL, it is possible to have word embedding as distributed word representations from textual data. The application of DL to aid Arabic ontology development remains largely unexplored. This paper investigates the performance of implementing DL with Arabic ontology learning tasks using major models such as Continuous Bag of Words (CBOW) and Skip-gram. Initial performance results are promising as an effective application of Arabic ontology learning.","PeriodicalId":20685,"journal":{"name":"Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90649040","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}