data scientists in software engineering seek insight in data collected from software projects to improve software development. The demand for data scientists with domain knowledge in software development is growing ra...
详细信息
ISBN:
(纸本)9781467330763
data scientists in software engineering seek insight in data collected from software projects to improve software development. The demand for data scientists with domain knowledge in software development is growing rapidly and there is already a shortage of such data scientists. data science is a skilled art with a steep learning curve. To shorten that learning curve, this workshop will collect best practices in form of data analysis patterns, that is, analyses of data that leads to meaningful conclusions and can be reused for comparable data. In the workshop we compiled a catalog of such patterns that will help experienced data scientists to better communicate about data analysis. The workshop was targeted at experienced data scientists and researchers and anyone interested in how to analyze data correctly and efficiently in a community accepted way.
The ever-increasing amount of unstructured data, including text, images, audio, and video, poses a serious challenge to traditional datamining techniques. machinelearning (ML) offers powerful tools and techniques to...
详细信息
This article explores the usefulness of the depth images provided by the current Microsoft Kinect sensors in different face analysis tasks including identity, gender and ethnicity. Four local feature extraction method...
详细信息
This article explores the usefulness of the depth images provided by the current Microsoft Kinect sensors in different face analysis tasks including identity, gender and ethnicity. Four local feature extraction methods (LBP, LPQ, HOG and BSIF) are investigated for both face texture and shape description. Extensive experiments on three publicly available Kinect face databases are reported. The experimental analysis yields into interesting findings. Furthermore, a comprehensive review of the literature on the use of Kinect depth data in face analysis is provided along with the description of the available databases. (C) 2015 Elsevier B.V. All rights reserved.
The proceedings contain 7 papers. The topics discussed include: how to teach a computer to learn about microbes: KG-COVID-19 and microbial graph learning;explaining multivariate time series forecasts: an application t...
The proceedings contain 7 papers. The topics discussed include: how to teach a computer to learn about microbes: KG-COVID-19 and microbial graph learning;explaining multivariate time series forecasts: an application to predicting the Swedish GDP;towards participatory design spaces for explainable ai interfaces in expert domains;teaching AI to explain its decisions can affect class balance;foundations for solving classification problems with quantitative abstract argumentation;sequential exceptional pattern discovery using pattern-growth: an extensible framework for interpretable machinelearning on sequential data;and a comparative study of explainer modules applied to automated skin lesion classification.
The proceedings contain 9 papers. The topics discussed include: why do sports officials dropout?;strategic patterns discovery in RTS-games for e-sport with sequential patternmining;maps for reasoning in ultimate;pred...
The proceedings contain 9 papers. The topics discussed include: why do sports officials dropout?;strategic patterns discovery in RTS-games for e-sport with sequential patternmining;maps for reasoning in ultimate;predicting the NFL using Twitter;use of performance metrics to forecast success in the national hockey league;finding similar movements in positional datastreams;comparison of machinelearning methods for predicting the recovery time of professional football players after an undiagnosed injury;predicting NCAAB match outcomes using ML techniques – some results and lessons learned;and key point selection and clustering of swimmer coordination through sparse Fisher-EM.
The proceedings contain 12 papers. The topics discussed include: validation of mixed-structured data using patternmining and information extraction;validation of knowledge-based systems through CommonKADS;composing t...
The proceedings contain 12 papers. The topics discussed include: validation of mixed-structured data using patternmining and information extraction;validation of knowledge-based systems through CommonKADS;composing tactical agents through contextual storyboards;an adaptable e-learning system for pupils with specific learning difficulties;decision-maker-aware design of descriptive datamining;validation of a datamining method for optimal university curricula;model-based software development - perspectives and challenges;a test case generation technique and process;from natural language requirements to a conceptual model;test case reduction methods by using CBR;and evolution support for model-based development and testing - summary.
In recent years, several ontological resources have been proposed to model machinelearning domain. However, they do not provide a direct link to linguistic data. In this paper, we propose a linguistic resource, a set...
详细信息
In recent years, several ontological resources have been proposed to model machinelearning domain. However, they do not provide a direct link to linguistic data. In this paper, we propose a linguistic resource, a set of several semantic frames with associated annotated initial corpus in machinelearning domain, we coined MLFrameNet. We have bootstrapped the process of (manual) frame creation by text mining on the set of 1293 articles from the machinelearning Journal from about 100 volumes of the journal. It allowed us to find frequent occurences of words and bigrams serving as candidates for lexical units and frame elements. We bridge the gap between linguistics analysis and formal ontologies by typing the frame elements with semantic types from the DMOP domain ontology. The resulting resource is aimed to facilitate tasks such as knowledge extraction, question answering, summarization etc. in machinelearning domain.
The proceedings contain 8 papers. The topics discussed include: a hybrid grid-based method for mining arbitrary regions-of-interest from trajectories;ensemble feature ranking for shellfish farm closure cause identific...
ISBN:
(纸本)9781450323697
The proceedings contain 8 papers. The topics discussed include: a hybrid grid-based method for mining arbitrary regions-of-interest from trajectories;ensemble feature ranking for shellfish farm closure cause identification;clustering household electricity use profiles;predicting petroleum reservoir properties from downhole sensor data using an ensemble model of neural networks;light-weight online predictive data aggregation for wireless sensor networks;and performance analysis of duty-cycling wireless sensor networks for train localization.
This paper presents a set of methods for the analysis of user activity and data preparation for the music recommender by the example of "Odnoklassniki"(1) social network. The history of actions is being anal...
详细信息
ISBN:
(纸本)9783319089799;9783319089782
This paper presents a set of methods for the analysis of user activity and data preparation for the music recommender by the example of "Odnoklassniki"(1) social network. The history of actions is being analyzed in multiple dimensions in order to find a number of collaborative and temporal correlations as well as to make the overall rankings. The results of the analysis are being exported in a form of a taste graph which is then used to generate on-line music recommendations. The taste graph displays relations between different entities connected with music (users, tracks, artists, etc.) and consists of the following main parts: user preferences, track similarities, artists' similarities, artists' works and demography profiles.
The deliberate misuse of technical infrastructure (including the Web and social media) for cyber deviant and cybercriminal behaviour, ranging from the spreading of extremist and terrorism related material to online fr...
详细信息
ISBN:
(纸本)9781450346757
The deliberate misuse of technical infrastructure (including the Web and social media) for cyber deviant and cybercriminal behaviour, ranging from the spreading of extremist and terrorism related material to online fraud and cyber security attacks, is on the rise. This workshop aims to better understand such phenomena and develop methods for tackling them in an effective and efficient manner The workshop brings together interdisciplinary researchers and experts in Web search, security informatics, social media analysis, machinelearning, and digital forensics, with particular interests in cyber security. The workshop programme includes refereed papers, invited talks and a panel discussion for better understanding the current landscape, as well as the future of datamining for detecting cyber deviance.
暂无评论