{"title":"A Deep Learning Framework to Predict Rating for Cold Start Item Using Item Metadata","authors":"Fahad Anwar, N. Iltaf, H. Afzal, Haider Abbas","doi":"10.1109/WETICE.2019.00071","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00071","url":null,"abstract":"Recommender systems improve browsing experience of users for large amount of items by assisting selection and classification of items utilizing item metadata. The performance of recommender system usually deteriorates when implicit data is used with limited user interaction history also regarded as cold start (CS) problem. This paper proposes a model to address cold start problem using content based technique where user or item metadata is used to break this ice barrier. The proposed method utilizes the feature extraction techniques (such as term frequencyInverse document frequency(TF-IDF)) and word embedding technique (Word2Vec). These content features are then used to predict the ratings for CS items by constructing user profiles using stacked auto-encoder. Experiments performed on largest real world dataset provided by Movielens 20M shows that proposed model outperforms the state-of-the-art approaches in CS item scenario.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121634765","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}
P. Ardimento, M. Bernardi, Marta Cimitile, G. D. Ruvo
{"title":"Mining Developer's Behavior from Web-Based IDE Logs","authors":"P. Ardimento, M. Bernardi, Marta Cimitile, G. D. Ruvo","doi":"10.1109/WETICE.2019.00065","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00065","url":null,"abstract":"The birth of cloud-based development environments makes available an increasing number of data coming out from the interaction of different developers with a diverse level of expertise. This data, if opportunely captured and analyzed, can be useful to understand how developers head the coding activities and can suggest members of developers community how to improve their performances. This paper presents a framework allowing to generate event logs from cloud-based IDE. These event logs are then examined using a process mining technique to extract the developers' coding processes and compare them in the shared coding environment. The approach can be used to discover emergent and interesting developers' behavior. Thus, we compare the coding process extracted by developers with different skills. To validate our approach, we describe the results of a study in which we investigate the coding activities of forty students of an advanced Java programming course performing a given programming task—during four assignments. Results also prove that users with different performances possess distinct attitudes highlighting that the adopted process mining technique can be useful to comprehend how developers can improve their coding skills.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121826306","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}
Wissem Eljaoued, N. Yahia, Narjès Bellamine Ben Saoud, C. Hanachi
{"title":"A Hybrid Recommendation Approach for Agent Organizational Structures","authors":"Wissem Eljaoued, N. Yahia, Narjès Bellamine Ben Saoud, C. Hanachi","doi":"10.1109/WETICE.2019.00011","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00011","url":null,"abstract":"The performance of an organization depends mainly on the performance of actors' coordination. In this paper, we consider coordination through organizational structures (OS) defined by roles and relations between them. The aim of this paper is to recommend performant OS combining Agent-based methodology with graph theory. The performance of an OS can be measured by different criteria such as robustness, flexibility and efficiency. However, the OS of an organization is not stable and could evolve through time in order to adapt to changes and perturbations of the environment. So, OS recommendations should be done not only at design time but also dynamically at run time. In this context, we propose a hybrid approach to recommend in a coherent way performant OS at these two different stages. At design time, from a set of roles and their authorized relationships, we recommend the most performing organizational structure corresponding to a trade-off between robustness, flexibility and efficiency. At run time, based on the monitoring of an organization structure and its evolution, we recommend OS adaptations to improve its performance. This approach has been implemented and evaluated through a crisis management case study where organization performance is of paramount importance.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127719069","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}
Marbilia Possagnolo Sergio, Talita de Souza Costa, M. Pessôa, P. S. Pedro
{"title":"A Semantic Approach to Support the Analysis of Abstracts in a Bibliographical Review","authors":"Marbilia Possagnolo Sergio, Talita de Souza Costa, M. Pessôa, P. S. Pedro","doi":"10.1109/WETICE.2019.00062","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00062","url":null,"abstract":"A large amount of scientific information is found in digital databases. This fact turns the search for the state of the art an increasingly challenging task. This work has the goal of developing a technological solution to support researchers in bibliographic review using the Latent Dirichlet Allocation. The Sw3T software, developed in Python, analyses the abstracts in scientific publications that interest the researcher. Through the use of semantic analysis, Sw3t supplies themes, which are defined by a group of terms. Themes can subsidize the researcher in the process of identification of complementary terms through the restriction on the number of publications of interest and it contributes to the analysis of the publications selected by their classification by theme as well. Sw3t has shown to be efficient and increased reliability in the search process regarding complementary terms, as well it contributes to the promptness of the detailed analysis of the publications. The results of the bibliographical review, regarding the application of Sw3T, have shown to be consistent and replicable. Future work will address the use of Sw3T for other bibliographic reviews as well as improvements and broadening of its functionalities such as search in DDB automation and previous content processing in abstracts.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132688412","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":"Autonomous Cars, 5G Mobile Networks and Smart Cities: Beyond the Hype","authors":"Fatma Raissi, Sami Yangui, F. Camps","doi":"10.1109/WETICE.2019.00046","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00046","url":null,"abstract":"This paper proposes one more slice of the next-generation self-driving automobile. It introduces an innovative and smart architecture that enables collaborative interactions between the autonomous cars and the urban devices available in the city. The aim of this architecture is to achieve the smart city vision where the different involved entities - such as cars, homes, citizens - exchange useful information and collaborate to reach common goals like decrease the traffic congestion. The proposed architecture sits at edges of 5G mobile telecommunication network and relies on 5G key enablers such as multi-access edge computing. A realistic use case that illustrates information exchange between an autonomous car and neighboring devices during a trip is provided. As for validation, a prototype implementing the use case was developed and evaluated. The lessons learned from the performed experiments are discussed.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130261800","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}
Luigi Sgaglione, L. Coppolino, S. D'Antonio, Giovanni Mazzeo, L. Romano, Domenico Cotroneo, Andrea Scognamiglio
{"title":"Privacy Preserving Intrusion Detection Via Homomorphic Encryption","authors":"Luigi Sgaglione, L. Coppolino, S. D'Antonio, Giovanni Mazzeo, L. Romano, Domenico Cotroneo, Andrea Scognamiglio","doi":"10.1109/WETICE.2019.00073","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00073","url":null,"abstract":"In the recent years, we are assisting to an undiminished, and unlikely to stop number of cyber threats, that have increased the organizations/companies interest about security concerns. Further, the rising costs of an efficient IT security staff and environment is posing a significant challenge. These have created a new fast growing trend named Managed Security Services (MSS). Often customers turn to MSS providers to alleviate the pressures they face daily related to information security. One of the most critical aspect, related to the outsourcing of security issues, is privacy. Security monitoring and in general security services require access to as much data as possible, in order to provide an effective and reliable service. It is the well known conflict between privacy and security, a particularly evident problem in security monitoring solutions. This paper analyzes a scenario of MSS in order to provide a privacy preserving solution that allows the security monitoring without violating the privacy requirements. The basic idea relies on the usage of the Homomorphic Encryption technology. Encrypting data using homomorphic schemes, cloud computing and MSS providers can perform different computations on encrypted data without ever having access to their decryption. This solution keeps data confidential and secured, not only during exchange and storage, but also during processing. We provide an ad-hoc Intrusion Detection System architecture for privacy preserving security monitoring, considering as counter threats Code Injection attacks on homomorphically encrypted fields.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115289168","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":"Complex Networks Monitoring and Security and Fraud Detection for Enterprises","authors":"K. Juszczyszyn, G. Kolaczek","doi":"10.1109/WETICE.2019.00034","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00034","url":null,"abstract":"The purpose of Complex Networks Monitoring and Security and Fraud Detection for Enterprises - CoNeSec track is two-fold: Firstly, the track offers a forum for scientists and engineers to exchange ideas on novel analytical techniques using network log data. Secondly, the track has a thematic focus on emerging technology for complex network, security and privacy. We seek publications on all theoretical and practical work in areas related to the theme above","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126760469","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":"WETICE 2019 - General Track","authors":"M. Rak","doi":"10.1109/WETICE.2019.00072","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00072","url":null,"abstract":"The International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises WETICE is an international forum for state-of the-art research in enabling technologies for collaboration. The 28th WETICE edition takes place on June 12-14, 2019 in Capri (Napoli), Italy and it is made of eleven scientific tracks.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122762762","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 Cloud Immune Security Model Based on Alert Correlation and Software Defined Network","authors":"R. Melo, D. D. J. D. Macedo","doi":"10.1109/WETICE.2019.00019","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00019","url":null,"abstract":"In this paper, we explore the AIS approach to develop an agent-based detection method to analyze network traffic. The system works in conjunction with attack graph based correlation and software-defined network (SDN) technology to mitigate attacks. In the correlation technique, alerts are correlated through an attack graph which improves detection performance by decreasing the false alert rate. The false alert reduction can avoid the negative effect that an SDN countermeasure can bring to the cloud Service Level Agreement (SLA) on the absence of threats. This work was tested for multi-step and distributed denial of service (DDoS) attacks. Results have shown the addition of the correlation technique can aid to the detection performance of AIS detection systems.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124581407","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":"Machine Learning of SPARQL Templates for Question Answering Over LinkedSpending","authors":"Roberto Cocco, M. Atzori, C. Zaniolo","doi":"10.1109/WETICE.2019.00041","DOIUrl":"https://doi.org/10.1109/WETICE.2019.00041","url":null,"abstract":"We present a Question Answering system aimed to answer natural language questions over the open RDF spending data provided by LinkedSpeding. We propose an original machine-learning approach to learn generalized SPARQL templates from an existing training set of (NL question, SPARQL query) pairs. In our approach, the generalized SPARQL templates are fed to an instance-based classifier that associates a given user-provided question to an existing pair that is used to answer the user question. We employ an external tagger, delegating the Named-Entity Recognition (NER) task to a service developed for the domain we want to query. The problem is particularly challenging due to the small training set size available, counting only 100 questions/SPARQL queries. We illustrate the results of our new approach using data provided by the Question Answering over Linked Data challenge (QALD-6) task 3, showing that we can provide a correct answer to 14 of the 50 questions of the test set. These results are then compared to existing systems, including our previous system, QA3, where templates were provided by an expert rather than being generated automatically from a training set.","PeriodicalId":116875,"journal":{"name":"2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115223927","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}