检索结果-内蒙古大学图书馆

Fourth IEEE International Conference on data Mining

作者： Stephan Bloehdorn Andreas Hotho Institute AIFB Knowledge Management Group University of Karlsruhe Karlsruhe Germany Knowledge and Data Engineering Group University of Kassel Kassel Germany

Document representations for text classification are typically based on the classical Bag-Of-Words paradigm. This approach comes with deficiencies that motivate the integration of features on a higher semantic level than single words. In this paper we propose an enhancement of the classical document representation through concepts extracted from background knowledge. Boosting is used for actual classification. Experimental evaluations on two well known text corpora support our approach through consistent improvement of the results.

关键词： Text categorization Boosting Ontologies data mining Tree data structures knowledge management data engineering Learning systems Information retrieval Frequency

来源：评论

学校读者我要写书评

暂无评论

Prediction of wastewater pre-precipitation variables using self-organizing networks

Prediction of wastewater pre-precipitation variables using s...

引用

20th IEEE International Symposium on Intelligent Control, ISIC '05 and the13th Mediterranean Conference on Control and Automation, MED '05

作者： Isaias, Padelis Nilsson, Sara Stathaki, Anna King, Robert E. IEEE Data and Knowledge Engineering Group Computer Research Institute Athens Greece Environmental Research Institute IVL Stockholm Sweden Electrical Engineering and Computer Science University of Patras Greece Computer Research Institute Athens Greece

This paper describes the derivation and design of an array of self-organizing networks trained by inductive learning for one step ahead prediction of the outputs of the pre-precipitation stage of a wastewater treatmen... 详细信息

ISBN: (纸本)0780389360

关键词： Wastewater

来源：评论

学校读者我要写书评

暂无评论

Ubicon: Observing Physical and Social Activities

Ubicon: Observing Physical and Social Activities

引用

IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Martin Atzmueller Martin Becker Stephan Doerfel Andreas Hotho Mark Kibanov Bjoern-Elmar Macek Folke Mitzlaff Juergen Mueller Christoph Scholz Gerd Stumme Knowledge and Data Engineering Group University of Kassel Germany Data Mining and Information Retrieval Group University of Würzburg Germany

ISBN: (纸本)9781467351461

The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.

关键词： data mining Context Software Social network services Educational institutions Radiofrequency identification Venus

来源：评论

学校读者我要写书评

暂无评论

Fact-Finding or Exploration: Identifying Latent Behavior Clusters in User’s Search Activities

Fact-Finding or Exploration: Identifying Latent Behavior Clu...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Johannes Schwerdt Michael Kotzyba Andreas Nürnberger Data Knowledge Engineering Group Otto von Guericke University Magdeburg Germany

Understanding the search behavior of users based on their current interaction with an information retrieval system, such as a search engine, can be quite beneficial to develop advanced support mechanisms. Statistical models comprise a rich framework for characterizing user's search behavior for known search activity classes but also for identifying unknown/latent search behavior clusters. To gather deeper insights of search activities, we apply Hidden Markov Models to classify search sessions of known search activities with an accuracy of 88.58% and derive behavioral properties of users from these models. Afterwards, we extend these models to Mixture Models and cluster the users' search behavior to reveal strong associations to the known search activities with an agreement of 79.1%, but also to identify new search behavior. That is, instead of just classifying already known search activities, our methodology also allows to identify new search activities solely on behavior parameters independent of the known search activities. Hence, in addition to qualitatively determined and evaluated search patterns, this statistical approach can be used to reveal new search activities from the data and therefore to further understand the human information seeking process. The method is suitable to detect new search behaviors as generic patterns in a latent parameter space. This enables the identification of user's search activities that might be triggered contradictory to the originally expected search behavior and/or can reveal behavioral sub patterns.

关键词： Task analysis Hidden Markov models Adaptation models data models Search engines Predictive models Markov processes

来源：评论

学校读者我要写书评

暂无评论

Towards Cross Site Personalisation

Towards Cross Site Personalisation

引用

IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Kevin Koidl Owen Conlan Vincent Wade Knowledge and Data Engineering Group (KDEG) School of Computer Science Dublin Ireland

Personalisation on the web is mostly confined to websites of online content providers. The main drawback of this approach is the missing consideration of the users previous cross-site browsing experience resulting in an often fragmented browsing experience. This paper introduces a service driven architecture for user-centric personalisation in online cross-site tasks. The goal of the architecture is twofold: (1) to provide non-intrusive personalised recommendations to the user by not interfering in their browsing freedom and (2) to introduce cross-site personalisation in a non-invasive manner, thus not interfering with the design and functionality of the overall website. We introduce the proposed architecture and its applicability across separately hosted open-source Web-based Content Management Systems (WCMS). We also discuss encouraging results of an initial task-based experiment concentrating on the user's perception of non-intrusive personalisation within and across different websites.

关键词： Computer architecture Taxonomy Content management Recommender systems Adaptation models Educational institutions Adaptive systems

来源：评论

学校读者我要写书评

暂无评论

XHATE-999: Analyzing and Detecting Abusive Language Across Domains and Languages 28

XHATE-999: Analyzing and Detecting Abusive Language Across D...

引用

28th International Conference on Computational Linguistics, COLING 2020

作者： Glavaš, Goran Karan, Mladen Vulić, Ivan Data and Web Science Group University of Mannheim Germany Text Analysis and Knowledge Engineering Lab. University of Zagreb Croatia Language Technology Lab. TAL University of Cambridge United Kingdom

ISBN: (纸本)9781952148279

We present XHATE-999, a multi-domain and multilingual evaluation data set for abusive language detection. By aligning test instances across six typologically diverse languages, XHATE-999 for the first time allows for disentanglement of the domain transfer and language transfer effects in abusive language detection. We conduct a series of domain- and language-transfer experiments with state-of-the-art monolingual and multilingual transformer models, setting strong baseline results and profiling XHATE-999 as a comprehensive evaluation resource for abusive language detection. Finally, we show that domain- and language-adaptation, via intermediate masked language modeling on abusive corpora in the target language, can lead to substantially improved abusive language detection in the target language in the zero-shot transfer setups. © 2020 COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference. All rights reserved.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

knowledge Cores in large formal contexts

arXiv

引用

arXiv 2020年

作者： Hanika, Tom Hirth, Johannes Knowledge and Data Engineering Group Dep. of Electrical Engineering and Computer Science University of Kassel

knowledge computation tasks are often infeasible for large data sets. This is in particular true when deriving knowledge bases in formal concept analysis (FCA). Hence, it is essential to come up with techniques to cope with this problem. Many successful methods are based on random processes to reduce the size of the investigated data set. This, however, makes them hardly interpretable with respect to the discovered knowledge. Other approaches restrict themselves to highly supported subsets and omit rare and interesting patterns. An essentially different approach is used in network science, called k-cores. These are able to reflect rare patterns if they are well connected in the data set. In this work, we study k-cores in the realm of FCA by exploiting the natural correspondence to bi-partite graphs. This structurally motivated approach leads to a comprehensible extraction of knowledge cores from large formal contexts data *** Codes 68T30 03G10 97R40 Copyright © 2020, The Authors. All rights reserved.

关键词： knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

Logsonomy - Social information retrieval with logdata 08

Logsonomy - Social information retrieval with logdata

引用

HYPERTEXT'08: 19th ACM Conference on Hypertext and Hypermedia 2008, HT'08

作者： Krause, Beate Hotho, Andreas Jäschke, Robert Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Wilhelmshoher Allee 73 34121 Kassel Germany Research Center L3S Appelstr. 9a 30167 Hannover Germany

ISBN: (纸本)9781595939852

Social bookmarking systems constitute an established part of the Web 2,0. in such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonornies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Today's search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user's information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance. This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonornies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a, large snapshot of *** and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics. Copyright 2008 ACM.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Academic publication management with PUMA - Collect, organize and share publications 1

引用

14th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2010

作者： Benz, Dominik Hotho, Andreas Jäschke, Robert Stumme, Gerd Halle, Axel Gerlach Sanches Lima, Angela Steenweg, Helge Stefani, Sven Knowledge and Data Engineering Group University of Kassel L3S Research Center Kassel D-34121 Germany University Library of Kassel Kassel D-34127 Germany Data Mining and Information Retrieval Group University of Würzburg Am Hubland Würzburg D-97074 Germany

ISBN: (数字)9783642154645

ISBN: (纸本)3642154638

The PUMA project fosters the Open Access movement und aims at a better support of the researcher's publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Information services

来源：评论

学校读者我要写书评

暂无评论

HardnessTesterV: A Web Machine Learning application for Vickers Hardness Prediction of a Metallic Alloy Using Flask API 4

HardnessTesterV: A Web Machine Learning application for Vick...

引用

4th International Conference on Electrical, Communication and Computer engineering, ICECCE 2023

作者： Olanipekun, Ayorinde Tayo Mashao, Daniel Data Science Across Disciplines Research Group Institute for the Future of Knowledge Faculty of Engineering and the Built Environment University of Johannesburg Auckland Park South Africa Faculty of Engineering and the Built Environment University of Johannesburg Auckland Park South Africa

ISBN: (纸本)9798350369694

This research presents the HardnessTesterV app- a web application for predicting the Vicker hardness of Laser welded Metallic alloy using Flask API, HTML, and CSS to build the front end and back end. Vickers hardness is an important property in the manufacturing industry, and predicting it accurately is vital for material selection and design. The Web application takes some of the important processing parameters as the input features and uses a random forest Machine learning model to predict its Vickers hardness. Flask API was used to create a RESTful interface that provides a user-friendly platform for users to submit the combinations of the processing parameters and receive predictions. HTML and CSS were used to design the front end of the web application to provide a visually appealing interface for users. The application was deployed on a PythonAnywhere cloud server, making it easily accessible to users. The application was deployed on a cloud server, making it easily accessible to users worldwide. The accuracy of the predictions was evaluated using various metrics and the results showed that the developed model can accurately predict the Vickers hardness of metallic alloys. HardnessTesterV web app measures the Vickers hardness of 2507 Duplex stainless steel material. The web application is expected to be a valuable tool for engineers and researchers in the manufacturing industry for material selection and design. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：