Multimediaminer: a system prototype for multimedia data mining. To protect your privacy, all features that rely on external API calls from your browser are turned off by default. last updated on 2020-10-15 21:51 CEST by the dblp team, all metadata released as open data under CC0 1.0 license, see also: Terms of Use | Privacy Policy | Imprint. {36} S. Deerwester, S. Dumais, G. Furnas, T. Landauer, and R. Harshman. Authoritative sources in a hyperlinked environment. In. {106} E. Riloff. {97} S. Nestorov, S. Abiteboul, and R. Motwani. In. The cluster-abstraction model: Unsupervised learning of topic hierarchies from text data. It is based on the idea that 'all citations are not created equal'. Feature selection for unbalanced class distribution and naïve bayes. : author identification using only citations. Richard Simon: Supervised analysis when the number of candidate features (p) greatly exceeds the number of cases (n). A data cleaning solution by Perl scripts for the KDD Cup 2003 task 2. Infering structure in semistructured data. Hammer, K. Ireland, Y. Papakonstantinou, J. Ullman, and J. Widom. {34} M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, mad S. Slattery. In. 31-36 Lijffijt, J., Kang, B., Puolamäki, K., & De Bie, T. (2016). Learning to classify english text with ilp methods. {71} H. Kargupta, I. Hamzaogiu, and B. Stafford. {59} S. Grumbach and G. Mecca. {122} W. Wiener, J. Pedersen, and A. Weigend. A machine learning approach to building domain-specific search engines. In. In. Tétrafusion: Information discovery on the internet. Supervised analysis when the number of candidate features (p) greatly exceeds the number of cases (n). {31} R. Cooley, B. Mobasher, and J. Srivastava. Agents that reduce work and information overload. Learning Missing Values from Summary Constraints X. Wu and D. Barbará (available in PDF and Postscript formats)ABSTRACT: Real-world data sets often contain errors and inconsistency.Even though this is a very important problem it has received relatively little attention in the research community. {61} A. Hauptmann. SIGKDD Exploration December 2005, Volume 7, Issue 2. "In vivo" spam filtering: a challenge problem for KDD. In, {99} G. Paliouras, C. Papatheodorou, V. Karkaletsis, P. Tzitziras, and C. D. Spyropoulos. Extraction patterns for information extraction tasks: A survey. Navigation pattern discovery from internet data. A query language for a web-site management system. {67} C.-N. Hsu and M.-T. Dung. {90} T. M. Mitchell. Mining the link structure of the world wide web. Text mining: The state of the art and the challenges. {88} A. McCallum, K. Nigam, J. Rennie, and K. Seymore. While we did signal Twitter to not track our users by setting the "dnt" flag, we do not have any control over how Twitter uses your data. In, {53} D. Freitag and A. McCallum. In. journal self-citations removed) received by a journal's published documents during the three previous years. Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal. In. It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is. Exploratory medical knowledge discovery: experiences and issues. Data mining for the web. Report on the conald workshop on learning from text and the web. In, {78} N. Kushmerick, D. Weld, and R. Doorenbos. In, {102} G. Piatetsky-Shapiro, R. Braachman, T. Khabaza, W. Kloesgen, and E. Simoudis. In. In search of the lost schema. Google Scholar Digital Library {89} T. Mitchell. Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. SIGKDD Exploration June 2007, Volume 9, Issue 1. * Required. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from Distributed data mining using an agent based architecture. {126} Y. Yang and J. Pedersen. The myth of the double-blind review? Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (pp. In, {128} O. R. Zaiane, J. Han, Z.-N. Li, S. H. Chee, and J. Chiang. {56} R. Goldman and J. Widom. In. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar. Copyright © 2020 ACM, Inc. {1} S. Abiteboul. In, {105} J. Rennie and A. McCallum. {9} P. Atzeni and G. Mecca. The users of Scimago Journal & Country Rank have the possibility to dialogue through comments linked to a specific journal. {33} J. Cowie and W. Lehnert. {21} J. Caxbonell, Y. Yang, and W. Cohen. {48} M. F. Fernandez, D. Floreseu, A. Y. Web mining: Information and pattern discovery on the world wide web. The lorel query language for semistructured data. For more information see our F.A.Q. Data mining in bioinformatics: report on BIOKDD'03. In. Querying semi-structured data. load references from crossref.org and opencitations.net. {51} E. Frank, G. W. Paynter, I. H. Witten, C. Gutwin, and C. G. Nevill-Manning. {47} D. Fensel, C. Knoblock, N. Kushmerick, and M.-C. Rousset. You need to opt-in for them to become active. In. Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. Automating the analysis and cataloging of sky surveys. Machine learning and data mining. Guest editors' introduction: Intelligent information retrieval. In, {104} A. Rauber and D. Merkl. The chart shows the ratio of a journal's documents signed by researchers from more than one country; that is including more than one country address. {70} H. L. K. Wang. {10} R. Baeza-Yates and e. Berthier Ribeiro-Neto. International Collaboration accounts for the articles that have been produced by researchers from several countries. Email(will not be published) This alert has been successfully added and will be sent to: You will be notified whenever a record that you have chosen has been cited. {91} D. Mladenic. Ua mutually beneficial integration of data mining and information extraction. Gene ranking using bootstrapped P-values. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy. Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. In R. Feldman, editor, {5} J. Allan, J. Carbonell, G. Doddington, J. Yamron, and Y. Yang. Intelligent agents for web-based tasks: An advice-taking approach. Presented at the ACM SIGKDD 2016 Full-day Workshop on Interactive Data Exploration and Analytics (IDEA). Domain-specific keyphrase extraction. In. Text-learning and related intelligent agents. Add open access links from to the list of external document links (if available). External citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents. Maintain the new SIGKDD and KDD Conference websites featuring state-of-art sharing and social media connections SIGKDD Impact Program supports projects that promote data science, increase its impact on society, and help the data science community. The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. Inductive learning algorithms and representations for text categorization. In. A declarative language for querying and restructuring the web. In, {6} J. Allan, R. Papka, and V. Lavrenko. SIGKDD Explorations, 1(2), 2000. {111} S. Soderland. Wrapper induction for semistructured, web-based information sources. Web usage mining: Discovery and applications of usage patterns from web data. {22} C. Cardie. {125} Y. Yang, J. Carbonell, R. Brown, T. Pierce, B. T. Archibald, and X. Liu. Webkdd-99: Workshop on web usage analysis and user profiling. In, {28} W.W. Cohen. About knowledge discovery in texts: A definition and an example. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. On knowledge discovery in graph-structured data. In. {11} M. Balabanovi'c and Y. Shoham. Mining association rules in multiple relations. At the same time, Twitter will persitently store several cookies with your web browser. Scalability and efficiency in multi-relational data mining. {118} S. Vaithyanathan. Information extraction with hmms and shrinkage. What can we learn from the web? In. In. Research issues in web data mining. In, {117} R. Uthurusamy. {113} J. Srivastava, R. Cooley, M. Deshpande, and P.-N. Tan. Extracting schema from semistructured data. {115} A.-H. Tan. Wrapper induction for information extraction. For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available). In, {94} I. Muslea, S. Minton, and C. Knoblock. Discovering trends in text databases. SIDE : a web app for interactive visual data exploration with subjective feedback. Accessibility of information on the web. In, {45} R. Feldman and I. Dagan. Introduction to information extraction technology. This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. Summary from the KDD-03 panel: data mining: the next 10 years. Introduction: Data mining on the internet. In. Graph-based relational learning: current and future directions. Special issue SIGKDD kali ini adalah tentang Link Mining. Special issue SIGKDD kali ini adalah tentang data mining untuk health informatics. Finding co-occurring text phrases by combining sequence and frequent set discovery. {121} S. M. Weiss, C. Apté, F. Damerau, D. E. Johnson, F. J. Oles, T. Goetz, and T. Hampp. Conference history. The anatomy of a large-scale hypertextual Web search engine. Empirical methods in information extraction. It is based on the idea that 'all citations are not created equal'. Loss-based estimation with cross-validation: applications to microarray data analysis. Approximate dataguides. {8} G. O. Arocena and A. O. Mendelzon. Technical Report Report RC-21570, IBM Research Report, 1999. {23} S. Chakrabarti. Software agents: A review. In Proceedings of the International Joint Conference on Artificial Intelligence IJCAI-99, pages 662-667, 1999. https://dl.acm.org/doi/10.1145/360402.360406. In L. M. Haas and A. Tiwary, editors, {98} K. Nigam, J. Lafferty, and A. McCallum. Knowledge discovery and data mining: toward a unifying framework. Predicting citation rates for physics papers: constructing features for an ordered probit model. Biological applications of multi-relational data mining. In. In. Follow us on @ScimagoJRScimago Lab, Copyright 2007-2020. In. Check if you have access through your login credentials or your institution to get full access on this article. Information extraction from html: Application of a general learning approach. {74} J. M. Kleinberg. {49} R. E. Filman and S. Pant. Improving classification of microarray data using prototype-based feature selection. Cut & paste. In, {17} S. Brin and L. Page. In F. N. Afrati and P. Kolaitis, editors. 86–95). Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Extracting semistructured information from the web. {2} S. Abiteboul, D. Quass, J. McHugh, J. Widom, and J. L. Wiener. So please proceed with care and consider checking the Internet Archive privacy policy. Learning approaches for detecting and tracking news events. Exploiting relational structure to understand publication patterns in high-energy physics. In, {79} L. Lakshmanem, F. Sadri, and I. Subramanian. Using reinforcement learning to spider the web efficiently. Websom - self-organizing maps of document collections. Mining association rules in hypertext databases. {50} D. Florescu, A. Y. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. A query language and optimization techniques for unstructured data. Add a list of references from , , and to record detail pages. In, {52} D. Freitag. In, {27} W.W. Cohen. The purpose is to have a forum in which general doubts about the processes of publication in the journal, experiences and other issues derived from the publication of papers are resolved. Discovering association of structure from semistructured objects. {112} M. Spiliopoulou. In, {39} S. Dumais, J. Platt, D. Heckerman, and M. Sahami. Microarray data mining: facing the challenges. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar. In, {75} Y. Kodratoff. {41} O. Etzioni. In, {116} H. Toivonen. the dblp computer science bibliography is funded by: Multi-relational data mining: an introduction. Text mining: A new frontier for lossless compression. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. Using maximum entropy for text classification. Graphical modeling based gene interaction analysis for microarray data. In. Levy, and D. Suciu. Integrating and using large databases of text, image, video and audio. So please proceed with care and consider checking the Twitter privacy policy. Text mining - knowledge extraction from unstructured textual data. For topics on particular articles, maintain the dialogue through the usual channels with your editor. In, {30} R. Cooley, B. Mobasher, and J. Srivastava. Intelligent internet systems. Untangling text data mining. From data mining to knowledge discovery: An overview. Conference papers of each Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining are published through ACM. In. {65} T. Honkela, S. Kaski, K. Lagus, and T. Kohonen. Add a list of citing articles from and to record detail pages. Data mining and the web: Past, present and future. {66} A. Houston, H. Chen, S. M. Hubbard, B. R. Schatz, T. D. Ng, R. R. Sewell, and K. M. Tolle. Applying data mining techniques for descriptive phrase extraction in digital document collections. {120} K. Wang and H. Liu. Learning information extraction rules for semi-structured and free text. We use cookies to ensure that we give you the best experience on our website. {37} L. Dehaspe and L. de Raedt. Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Indexing by latent semantic analysis. Special issue of machine learning on information retrieval introduction. In, {93} I. Muslea. The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. EqRank: a self-consistent equivalence relation on graph vertexes. Advances in predictive model generation for data mining. Text mining at the term level. State of the art of graph-based data mining. {127} O. Zaïane and J. Han. A hybrid user model for news story classification. In E. A. Ada beberapa paper dan survey tentang link mining (berupa file PDF) Ada juga beberapa report KDDCup, workshop, serta laporan Interview dengan Usama Fayyad (Yahoo! Evolution of the number of total citation per document and external citation per document (i.e. {25} S. Chakrabarti, B. Dom, and P. Indyk. In L. M. Haas and A. Tiwary, editors, {26} S. Chawathe, H. Garcia-Molina, J. {35} F. Crimmins, A. Smeaton, T. Dkaki, and J. Mothe. {12} A. Büchner, M. Baumgarten, S. Anand, M. Mulvenna, and J. Hughes. The world wide web: Quagmire or gold mine. In. {3} H. Ahonen, O. Heinonen, M. Klemettinen, and A. Verkamo. The Download Estimation task on KDD Cup 2003. In M. Jarke, M. J. Carey, K. R. Dittrich, F. H. Lochovsky, P. Loucopoulos, and M. A. Jeusfeld, editors, {57} R. Goldman and J. Widom. Data Source: Scopus®. Privacy notice: By enabling the option above, your browser will contact twitter.com and twimg.com to load tweets curated by our Twitter accout. Improved algorithms for topic distillation in a hyperlinked environment. Evolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years. In, {80} P. Langley. Fox, P. Ingwersen, and R. Fidel, editors, {108} S. Scott and S. Matwin. Dataguides: Enabling query formulation and optimization in semistructured databases. Multi-relational data mining: the current frontiers. Little words can make a big difference for text classification. Levy and D. S. Weld. In, {46} R. Feldman, M. Fresko, Y. Kinar, Y. Lindell, O. Liphstar, M. Rajman, Y. Schler, and O. Zamir. Model Builder for Predictive Analytics & Fair Isaac's approach to KDD Cup 2003. {64} S. J. Hong and S. M. Weiss. In, {13} K. Bharat and M. R. Henzinger. {84} A. Y. In, All Holdings within the ACM Digital Library. Citation prediction using time series approach KDD Cup 2003 (task 1). In, {60} J. In, {63} T. Hofmann. Multirelational data mining 2003: workshop report. On-line new event detection and tracking. In, {109} L. Singh, B. Chen, R. Haight, P. Scheuermann, and K. Aoki. Statistical methods for joint data mining of gene expression and DNA sequence database. Prospects and challenges for multi-relational data mining. Automatic labeling of self-organizing maps: Making a treasure-map reveal its secrets. A machine learning approach to building domain-specific search engines. In, {44} U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. Feature engineering for text classification. Generating finite-state transducers for semi-structured data extraction from the web. Schema discovery for semistructured data. {58} S. Green, L. Hurst, B. Nangle, P. Cunningham, F. Somers, and R. Evans. Enhanced hypertext categorization using hyperlinks. {62} M. A. Hearst. {82} Iberto O. Mendelzon, G. A. Mihalla, and T. Milo. Google Scholar Digital Library {88} A. McCallum, K. Nigam, J. Rennie, and K. Seymore. In, {40} J. S. T. Eliassi-Rad. Link mining: a new data mining challenge. In. A robust system architecture for mining semistructured data. {68} T. Joachims, D. Freitag, and T. Mitchell. {86} P. Maes. Large-scale mining of usage data on web sites. {4} H. Ahonen, O. Heinonen, M. Klemettinen, and A. Verkamo. In, {16} J. Borges and M. Levene. Weboql: Restructuring documents, databases, and webs. Fab: Content-based, collaborative recommendation. In. Classification of heterogeneous gene expression data. In, {83} B. The hidden web. In, {29} W. W. Cohen. Modeling subjective uncertainty in image annotation. Searching the internet - guest editors' introduction. User modeling in adaptive interfaces. Towards interactive exploration of gene expression patterns. Using unsupervised link discovery methods to find interesting facts and connections in a bibliography dataset. In, {14} D. Billsus and M. Pazzani. KDD-2003 workshop on data mining standards, services and platforms (DM-SSP 03). In H. V. Jagadish and I. S. Mumick, editors, {20} J. Carbonell, M. Craven, S. Fienberg, T. Mitchell, and Y. Yang. Workshop on intelligent information integration (iii'99). Data mining of user navigation patterns. {42} U. Fayyad, S. Djorgovski, and N. Weir. In. Webml: Querying the world-wide web for resources and knowledge. In. A neural network approach to topic spotting. {110} P. Smyth, U. M. Fayyad, M. C. Burl, and P. Perona. Ada beberapa paper tentang topik ini. In, {95} U. Y. Nahm and R. J. Mooney. Database techniques for the world-wide web: A survey. {87} B. Masand and M. Spiliopoulou. In, {54} J. Fürnkranz. Meta-clustering of gene expression data and literature-based information. The ACM Digital Library is published by the Association for Computing Machinery. In, {43} U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. {85} S. K. Madria, S. S. Bhowmick, W. K. Ng, and E.-P. Lira. {19} P. Buneman, S. B. Davidson, G. G. Hillebrand, and D. Suciu. Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those not cited during the following year. {81} S. Lawrence and C. L. Giles. Trawling the web for emerging cybercommunities. Selain itu, ada juga artike… Request PDF | On Sep 25, 2014, Charu C. Aggarwal and others published ACM SIGKDD Explorations Newsletter - Special issue on big data | Find, read and cite all the research you need on ResearchGate Maximizing text-mining performance. {96} S. Nestorov, S. Abiteboul, and R. Motwani. Some practical observations on integration of web information. In, {76} S. R. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. Data mining for hypertext: A tutorial survey. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. Hammer, H. Garcia-Molina, J. Cho, A. Crespo, and R. Aranha. Machine learning methods applied to DNA microarray data can improve the diagnosis of cancer. Levy, and A. O. Mendelzon. The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Querying the world wide web. In, {7} D. E. Appelt and D. Israel. Technical Report TCD-CS-1997-06, Technical Report of Trinity College, University of Dublin, 1997. {72} H. Kautz, B. Selman, and M. Shah. In, {103} M. Rajman and R. Besançon. In, {69} M. Junker, M. Sintek, and M. Rinck. To manage your alert preferences, click on the button below. {24} S. Chakrabarti, B. Dora, D. Gibson, J. Kleinberg, S. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. In, {124} I. H. Witten, Z. Bray, M. Mahoui, and W. J. Teahan. A novel approach to determine normal variation in gene expression data. An overview of issues in developing industrial data mining and knowledge discovery applications. The tsimmis project: Integration of heterogeneous information sources. From data mining to knowledge discovery: Current challenges and future directions. In, {15} J. Borges and M. Levene. Differential expression, class discovery and class prediction using S-PLUS and S+ArrayAnalyzer. Information extraction. Resolving citations in a paper repository. Learning for text categorization and information extraction with ilp. Medical data mining on the internet: Research on a cancer information system. Learning to extract symbolic knowledge from the world wide web. Exploiting structural information for text classification on the www. Knowledge discovery in textual databases (kdt). In, {55} M. N. Garofalakis, R. Rastogi, S. Seshadri, and K. Shim. Lent, R. Agrawal, and R. Srikant. Topic detection and tracking pilot study: Final report. Machine learning in low-level microarray analysis. {92} D. Mladenic and M. Grobelnik. Mining biologically active patterns in metabolic pathways using microarray expression profiles. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric. Data preparation for mining world wide web browsing patterns. All settings here will be stored as cookies with your web browser. Webwatcher: A tour guide for the world wide web. Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. those documents other than research articles, reviews and conference papers.