This handbook presents a thorough overview in 45 chapters from more than 100 renowned experts in the field. It provides the tools to help overcome the problems of video storage, cataloging, and retrieval, by exploring content standardization and other content classification and analysis methods. The challenge of these complex problems make this book a must-have for video database practitioners in the fields of image and video processing, computer vision, multimedia systems, data mInIng, and many other diverse disciplines. Topics include video segmentation and summarization, archiving and retrieval, and modeling and representation.
標簽： handbook chapters presents overview
上傳時間： 2013-12-15
上傳用戶：yuzsu
隨著計算機、網(wǎng)絡(luò)技術(shù)的發(fā)展，獲得有關(guān)資料非常簡單易行。但對于數(shù)量大、涉及 面寬的數(shù)據(jù)，傳統(tǒng)統(tǒng)計方法無法完成這類數(shù)據(jù)的分析。因此，一種智能化的、綜合應(yīng)用各種統(tǒng)計分析、數(shù)據(jù)庫、智能語言來分析龐大數(shù)據(jù)資料的“數(shù)據(jù)挖掘” (Date mInIng)技術(shù)應(yīng)運而生。本文主要介紹了數(shù)據(jù)挖掘的基本概念以及數(shù)據(jù)挖掘的方法；本文對數(shù)據(jù)挖掘的應(yīng)用及其發(fā)展前景也進行了描述。
標簽： 計算機 網(wǎng)絡(luò)技術(shù) 發(fā)展
上傳時間： 2014-01-01
上傳用戶：851197153
用VC++實現(xiàn)apriori演算法，可以找尋Frequent Itemsets，用途於Data mInIng是很具參考價值
上傳時間： 2013-12-17
上傳用戶：liglechongchong
Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering techniques that are frequently used in data mInIng have been developed in machine learning research community. Frequent pattern and association rule mInIng is one of the few excep- tions to this tradition. The introduction of this technique boosted data mInIng research and its impact is tremendous. The algorithm is quite simple and easy to implement. Experimenting with Apriori-like algorithm is the fi rst thing that data miners try to do.
標簽： 64257 algorithms decision pattern
上傳時間： 2014-01-12
上傳用戶：wangdean1101
一個自然語言處理的Java開源工具包。LingPipe目前已有很豐富的功能，包括主題分類（Top Classification）、命名實體識別（Named Entity Recognition）、詞性標注（Part-of Speech Tagging）、句題檢測（Sentence Detection）、查詢拼寫檢查（Query Spell Checking）、興趣短語檢測（Interseting Phrase Detection）、聚類（Clustering）、字符語言建模（Character Language Modeling）、醫(yī)學文獻下載/解析/索引（MEDLINE Download, Parsing and Indexing）、數(shù)據(jù)庫文本挖掘（Database Text mInIng）、中文分詞（Chinese Word Segmentation）、情感分析（Sentiment Analysis）、語言辨別（Language Identification）等API。
上傳時間： 2013-12-04
上傳用戶：15071087253
nearest neighbour clustering is an algoithm that puts data in categories. This algotithm is a data mInIng subject. Similar data is put in the same cluster.
標簽： data clustering categories algotithm
上傳時間： 2017-03-27
上傳用戶：181992417
電子書，作者：Soumen Chakrabarti。書名：mInIng the Web --- Discovering Knowledge from Hypertext Data
標簽： 電子書
上傳時間： 2017-05-10
上傳用戶：84425894
A guide to Matlab for Beginners and experienced users, A Guide to MATLAB Object Oriented Programming, The Handbook Of Data mInIng, Matlab - Creating Graphical User Interfaces,
標簽： Programming experienced Beginners Oriented
上傳時間： 2017-06-12
上傳用戶：cccole0605
This volume presents the state of the art concerning quality and interestingness measures for data mInIng. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.
標簽： interestingness concerning the presents
上傳時間： 2014-01-19
上傳用戶：ve3344
The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mInIng algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mInIng algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local memory-based models. The third section shows how all of the preceding analysis fits together when applied to real-world data mInIng problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
標簽： foundations The consists sections
上傳時間： 2017-06-22
上傳用戶：lps11188
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