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检索条件"任意字段=11th ACM International Conference on Web Search and Data Mining"

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Spectral Bloom Filters for Client Side search

Spectral Bloom Filters for Client Side Search

引用

international conference and Workshop on Computing and Communication (IEMCON)

作者： Parth Parikh Mrunank Mistry Dhruvam Kothari Sunil Khachane Rajiv Gandhi Institute of Technology Mumbai India

the following topics are dealt with: learning (artificial intelligence); Internet of things; convolutional neural nets; feature extraction; object detection; Internet; data mining; cloud computing; pattern classificat... 详细信息

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

关键词： Memory management Information filters Probabilistic logic Mobile communication Mobile applications Indexes Information technology

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To Recognize Families In the Wild: A Machine Vision Tutorial 18

To Recognize Families In the Wild: A Machine Vision Tutorial

引用

26th acm Multimedia conference (MM)

作者： Robinson, Joseph P. Shao, Ming Fu, Yun Northeastern Univ Boston MA 02115 USA UMass Dartmouth Dartmouth MA 02747 USA

ISBN: (纸本)9781450356657

Automatic kinship recognition has relevance in an abundance of applications. For starters, aiding forensic investigations, as kinship is a powerful cue that could narrow the search space (e.g., knowledge that the "Boston Bombers" were brothers could have helped identify the suspects sooner). In short, there are many beneficiaries that could result from such technologies: whether the consumer (e.g., automatic photo library management), scholar (e.g., historic lineage & genealogical studies), data analyzer (e.g., social-media-based analysis), investigator (e.g., cases of missing children and human trafficking- for instance, it is unlikely that a missing child found online would be in any database, however, more than likely a family member would be), or even refugees. Besides application-based problems, and as already hinted, kinship is a powerful cue that could serve as a face attribute capable of greatly reducing the search space in more general face-recognition problems. In this tutorial, we will introduce the background information, progress leading us up to these points, several current state-of-the-art algorithms spanning various views of the kinship recognition problem (e.g., verification, classification, tri-subject). We will then cover our large-scale Families In the Wild (FIW) image collection, several challenge competitions it as been used in, along with the top performing deep learning approaches. the tutorial will end with a discussion about future research directions and practical use-cases.

关键词： Visual kinship understanding family recognition deep learning familiar feature big data

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Malware detection based on directed multi-edge dataflow graph representation and convolutional neural network

Malware detection based on directed multi-edge dataflow grap...

引用

international conference on Knowledge and Systems Engineering

作者： Nguyen Viet Hung Vu Dinh Phai Pham Ngoc Dung Qi Shi Tran Nguyen Ngoc Faculty of Information Technology Le Quy Don Techincal University Hanoi Viet Nam Faculty of Engineering and Technology Liverpool John Moore University Liverpool England

In recent years, malware has grown constantly in both quantity and complexity. Traditional malware detection methods such as string search, hash code comparison, etc. have to face the challenging appearance of more and more new malware variations. One of the most promising approaches to tackling them is to use machine learning techniques to automatically analyze and detect unknown malicious softwares. In this paper, we introduce a novel method of using dynamic behavior data to represent malicious code in the form of multi-edge directed quantitative data flow graphs and a deep learning technique to detect malicious code. Our experimental result shows that the proposed method archived a higher detection rate than other machine learning methods, and a higher unknown malware detection rate, compared with commercial antivirus software.

关键词： Malware Feature extraction Machine learning Convolutional neural networks data mining Sockets

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Flint: Google-basing the web 08

Flint: Google-basing the Web

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Proceedings of the 11th international conference on Extending database technology: Advances in database technology

作者： Lorenzo Blanco Valter Crescenzi Paolo Merialdo Paolo Papotti Roma Tre University - Italy

ISBN: (纸本)9781595939265

Several web sites deliver a large number of pages, each publishing data about one instance of some real world entity, such as an athlete, a stock quote, a book. Even though it is easy for a human reader to recognize these instances, current search engines are unaware of them. Technologies for the Semantic web aim at achieving this goal; however, so far they have been of little help in this respect, as semantic publishing is very *** have developed a system, called Flint, for automatically searching, collecting and indexing web pages that publish data representing an instance of a certain conceptual entity. Flint takes as input a small set of labeled sample pages: it automatically infers a description of the underlying conceptual entity and then searches the web for other pages containing data representing the same entity. Flint automatically extracts data from the collected pages and stores them into a semi-structured self-describing database, such as Google Base. Also, the collected pages can be used to populate a custom search engine; to this end we rely on the facilities provided by Google Co-op.

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that's 'é' not 'þ' '?' or '◓': a user-driven context-aware approach to erroneous metadata in digital libraries 11

That's 'é' not 'þ' '?' or '◓': a user-driven context-awar...

引用

Proceedings of the 11th annual international acm/IEEE joint conference on Digital libraries

作者： David Bainbridge Michael B. Twidale David M. Nichols University of Waikato Hamilton New Zealand University of Illinois Urbana-Champaign USA

ISBN: (纸本)9781450307444

In this paper we present a novel system for user-driven integration of name variants when interacting with web-based information systems. the growth and diversity of online information means that many users experience disambiguation and collocation errors in their information searching. We approach these issues via a client-side JavaScript browser extension that can reorganise web content and also integrate remote data sources. the system is illustrated through three worked examples using existing digital libraries.

关键词： selective web editability name authority control crowdsourcing

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mining Performance Regression Inducing Code Changes in Evolving Software

Mining Performance Regression Inducing Code Changes in Evolv...

引用

international mining Software Repositories, MSR

作者： Qi Luo Denys Poshyvanyk Mark Grechanik College of William and Mary University of Illinois at Chicago

ISBN: (纸本)9781509022427

During software evolution, the source code of a system frequently changes due to bug fixes or new feature requests. Some of these changes may accidentally degrade performance of a newly released software version. A notable problem of regression testing is how to find problematic changes (out of a large number of committed changes) that may be responsible for performance regressions under certain test inputs. We propose a novel recommendation system, coined as PERFIMPACT, for automatically identifying code changes that may potentially be responsible for performance regressions using a combination of search-based input profiling and change impact analysis techniques. PERFIMPACT independently sends the same input values to two releases of the application under test, and uses a genetic algorithm to mine execution traces and explore a large space of input value combinations to find specific inputs that take longer time to execute in a new release. Since these input values are likely to expose performance regressions, PERFIMPACT automatically mines the corresponding execution traces to evaluate the impact of each code change on the performance and ranks the changes based on their estimated contribution to performance regressions. We implemented PERFIMPACT and evaluated it on different releases of two open-source web applications. the results demonstrate that PERFIMPACT effectively detects input value combinations to expose performance regressions and mines the code changes are likely to be responsible for these performance regressions.

关键词： Software Testing Genetic algorithms data mining Degradation Stakeholders Fuel processing industries

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Intrusion classification using ECLAT and Fuzzy Logic

Intrusion classification using ECLAT and Fuzzy Logic

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international conference on Computing and Networking Technology (ICCNT)

作者： Asif Ahamad P. S. Jeevaraj ABV-IIITM Gwalior India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

In today's world with the increase in internet usage, every digital gadget is getting connected to the internet. Due to the open connectivity of the internet, devices connected to the internet are exposed to the disturbances caused by masqueraders, misfeasors, malware writers, and intruders. Researchers are in the continuous search of methods to detect the attacks in the network and to introduce these methods to the low computation capability devices. In this work, it aimed at creating a disruption sensing system for identifying the disturbances caused by intruders. It will be achieved by choosing the best traffic capturing component. then, by introducing/improving the association rule mining algorithm to identify the patterns in the data and to generate better rules. then, by using the proposed method based on fuzzy logic and inference system to help in identifying the attack.

关键词： Fuzzy logic Intrusion detection data mining Tools Genetic algorithms Artificial intelligence Clustering algorithms

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Development of Creative thinking Support Method through Text mining for Inspiration

Development of Creative Thinking Support Method through Text...

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international Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Koji Okuhara Takeshi Matsui Yuki Yamamoto Toyama Prefectural University Imizu Toyama Japan Faculty of Social and Information Studies Gunma University Maebashi Gunma Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

In this study, for multiple keywords, we collect text data on those keywords from cyberspace by crawling and scraping. then, natural language processing is used to reduce the text data to word groups of nouns that are considered to be important, and the importance of each word is calculated from the transition probability between words, and a network is generated. In addition, we construct a system to support idea generation by drawing 3D directed graphs to check the strength of word associations from arbitrary viewpoints.

关键词： three-dimensional displays Plastics Internet Directed graphs Damping Text mining search engines

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Time Series data mining: A Unifying View

Time Series Data Mining: A Unifying View

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international conference on data Science and Advanced Analytics (DSAA)

作者： Eamonn Keogh University of California Riverside Riverside California USA

ISBN: (数字)9798350364941

ISBN: (纸本)9798350364958

Time series data are ubiquitous; large volumes of such data are routinely created in scientific, industrial, entertainment, medical and biological domains. Examples include ECG data, gait analysis, stock market quotes, machine health telemetry, search engine throughput volumes etc. What do we want to do with such time series? Everything! Classification, clustering, joins, anomaly detection, motif discovery, similarity search, visualization, summarization, compression, segmentation, rule discovery etc. Rather than a deep dive in just one of these subtopics, in this tutorial I will show a surprisingly small set of high-level representations, definitions, distance measures and primitives can be combined to solve the first 90 to 99.9% of the problems listed above. the tutorial will be illustrated with numerous real-world examples created just for this tutorial, including examples from robotics, wearables, medical telemetry, astronomy, and (especially) animal behavior. Moreover, all sample datasets and code snippets will be released so that the tutorial attendees (and later, readers) can first reproduce the results demonstrated, before attempting similar analysis on their data.

关键词： Time series analysis Tutorials search engines Gain measurement throughput search problems Telemetry Wearable devices Stock markets Robots

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Correspondence from color shading

Correspondence from color shading

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international conference on Pattern Recognition

作者： H.H. Nguyen P. Cohen Perception and Robotics Laboratory Ecole Polytechnique Montreal QUE Canada

Presents a region-based matching algorithm, working on the color shading information (red, green and blue) contained in an image pair. In each color image, the regions are defined as connected areas within which the shading surface (i.e. the surface whose height at each location equals the color brightness in the image) maintains constant-sign Gaussian and mean curvatures. Region characteristics and adjacency information are explored by means of a region graph, in which each node corresponds to a particular region and is labeled with a vector of intraregional characteristics, while the arc joining two adjacent nodes is labeled with the relative position of the corresponding regions. the search for correspondences is restricted by means of a curvature consistency constraint, which states that matching regions must be embedded in areas of the shading surfaces having similar curvature characteristics. the disparity maps extracted from the R, G and B signals are combined at each resolution level of a coarse-to-fine strategy.< >

关键词： Color Surface morphology data mining Robots Laboratories Image resolution Signal resolution Image matching Image edge detection Image segmentation

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