2017 Intelligent Systems Conference (IntelliSys)最新文献

Financial Discussion Boards Irregularities Detection System (FDBs-IDS) using information extraction 基于信息提取的金融论坛违规检测系统(fdb - ids)

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-07 DOI: 10.1109/INTELLISYS.2017.8324262

M. Owda, Pei Shyuan Lee, Keeley A. Crockett

{"title":"Financial Discussion Boards Irregularities Detection System (FDBs-IDS) using information extraction","authors":"M. Owda, Pei Shyuan Lee, Keeley A. Crockett","doi":"10.1109/INTELLISYS.2017.8324262","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324262","url":null,"abstract":"The current growth and the technology used in global stock markets has created unprecedented opportunities for the individuals and businesses to access capital and grow and diversify their portfolios. Individuals nowadays can decide to invest and act in few minutes if not in few seconds. This growth has led to a corresponding growth in the amount of fraud and misconduct seen in the stock markets through the use of technology. The internet is often used as a real time platform for illegal financial activity such as illegal activities on Financial Discussion Boards (FDBs). Managing and monitoring FDBs in real time is a complex and time consuming task; given the volume of data produced and the fact that some of the data is unstructured. This paper presents a novel Financial Discussion Boards Irregularities Detection System (FDBs-IDS) for FDBs which can highlight irregularities or potentially unlawful practices on FDBs. For example comments that might suggest a pump and dump activity is happening. The proposed system extracts information from FDBs, where templates hosting scenarios of known illegal activities are used to detect any potential misdemeanors. Analysis conducted on a single day trading, found that of the 3000 comments extracted from FDBs, 0.2% of these comments were deemed suspicious and required further investigation of a discussion board moderator. The manpower required to perform this task manually over the course of a year could be excessive and unaffordable. This research highlights the importance and the need of an automated crime detection system on FDBs, such as FDBs-IDS which could be used and thus tackle potential criminal activities on the internet.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116004795","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}

引用次数: 8

Evaluating cross domain sentiment analysis using supervised machine learning techniques 使用监督机器学习技术评估跨域情感分析

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-07 DOI: 10.1109/INTELLISYS.2017.8324369

A. Aziz, A. Starkey, Marcus Campbell Bannerman

引用次数: 9

Towards stream-based reasoning and machine learning for IoT applications 面向物联网应用的基于流的推理和机器学习

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-07 DOI: 10.1109/INTELLISYS.2017.8324292

M. Endler, Jean-Pierre Briot, Francisco Silva e Silva, V. P. De Almeida, E. Haeusler

{"title":"Towards stream-based reasoning and machine learning for IoT applications","authors":"M. Endler, Jean-Pierre Briot, Francisco Silva e Silva, V. P. De Almeida, E. Haeusler","doi":"10.1109/INTELLISYS.2017.8324292","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324292","url":null,"abstract":"As distributed IoT applications become larger and more complex, the pure processing of raw sensor and actuation data streams becomes impractical. Instead, data streams must be fused into tangible facts and these pieces of information must be combined with a background knowledge to infer new pieces of knowledge. And since many IoT applications require almost realtime reactivity to stimulus of the environment, such information inference process has to be performed in a continuous, on-line manner. This paper proposes a new semantic model for data stream processing and real-time reasoning based on the concepts of Semantic Stream and Fact Stream, as a natural extension of Complex Event Processing (CEP) and RDF (graph-based knowledge model). The main advantages of our approach are that 1) it considers time as a key relation between pieces of information; 2) the processing of streams can be implemented using CEP; 3) it is general enough to be applied to any Data Stream Management System (DSMS). Lastly, we will present challenges and prospects on using machine learning and induction algorithms to learn abstractions and reasoning rules from a continuous data stream.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"1965 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128038070","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}

引用次数: 12

Crack detection in concrete elements from RGB pictures using modified line detection Kernels 基于改进线检测核的RGB图像混凝土构件裂纹检测

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324222

Luis Alberto Sánchez Calderón, J. Bairán

引用次数: 8

Hybridization of moth flame optimization and gravitational search algorithm and its application to detection of food quality 蛾焰优化与引力搜索算法的杂交及其在食品质量检测中的应用

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324318

A. Sarma, A. Bhutani, Lavika Goel

引用次数: 17

A smart lighting system using wireless sensor actuator network 一种采用无线传感器致动器网络的智能照明系统

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324294

Lwin Myo Thet, Arun Kumar, N. Xavier, S. K. Panda

引用次数: 8

Hand signature and handwriting recognition as identification of the writer using gray level cooccurrence matrix and bootstrap 采用灰度共生矩阵和自举法对手写签名进行识别

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324267

Lely Hiryanto, A. Yohannis, Teny Handhayani

引用次数: 5

Classification of imbalanced data in E-commerce 电子商务中不平衡数据的分类

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324212

Liliya I. Besaleva, A. Weaver

{"title":"Classification of imbalanced data in E-commerce","authors":"Liliya I. Besaleva, A. Weaver","doi":"10.1109/INTELLISYS.2017.8324212","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2017.8324212","url":null,"abstract":"Applications for machine learning algorithms are beginning to dominate the world of online commerce with their seemingly endless potential for supplementing fully customizable shopping experiences. From socially impactful event predictions to smarter ways of shopping online, big fast data is streaming in and being utilized constantly. Unfortunately, unusual instances of data, called imbalanced data, are still being ignored at large because of the inadequacies of analytical methods that are designed to handle homogenized data sets and to “smooth out” outliers. Consequently, rare use cases of significant importance remain neglected and lead to high-cost loses or even tragedies. In the past decade, a myriad of approaches handling this problem that range from data modifications to alterations of existing algorithms have appeared with varying success. Yet, the majority of them have major drawbacks when applied to different application domains because of the non-uniform nature of the applicable data. Within the vast domain of e-Commerce, we are proposing a new approach for handling imbalanced data, which is a hybrid classification method that will consist of a mixed solution of multi-modal data formats and algorithmic adaptations for an optimal balance between prediction accuracy, precision and specificity. Our solution improves data usability, classification accuracy and resulting costs of analyzing massive data sets used in personalizing customer experiences in e-Commerce.","PeriodicalId":131825,"journal":{"name":"2017 Intelligent Systems Conference (IntelliSys)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123525865","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}

引用次数: 4

Discovering news events that move markets 发现影响市场的新闻事件

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324333

Yu.L. Gurin, Terrence Szymanski, Mark T. Keane

引用次数: 2

Information compression, multiple alignment, and intelligence 信息压缩、多重对齐、智能化

2017 Intelligent Systems Conference (IntelliSys) Pub Date : 2017-09-01 DOI: 10.1109/INTELLISYS.2017.8324252

J. Gerard Wolff

引用次数: 0