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商品描述
There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob.
In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users.
Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches.
This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit.
Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard.
商品描述(中文翻譯)
在群眾中有著豐富的智慧,但如何在一千人同時交談的情況下傾聽呢?識別網路使用者的需求、想法和知識就像是在聆聽一群人。
在 Web 2.0 時代,利用使用者貢獻、互動和反饋的集體力量是市場主導的關鍵。一種新的強大程式設計技術類別讓你能夠發現人們在瀏覽網站、發表部落格和與其他使用者互動時所留下的數據中鎖定的模式、相互關係和個人檔案——這就是集體智慧。
《集體智慧實踐》是一本實用指南,旨在使用 Java 實現集體智慧的概念。這是第一本基於 Java 的書籍,強調關鍵數據收集和挖掘技術的基本演算法和技術實現,如分析趨勢、發現關係和進行預測。它通過將基於內容的分析與協作方法相結合,提供了一種務實的個性化方法。
本書適合在實際高使用率應用中實現集體智慧的 Java 開發者。通過一個運行範例,你將學習如何從部落格中收集和使用資訊,並開發可以嵌入自己應用程式中的軟體。這些程式碼範例可以立即重用,為 Java 開發者提供了一個可用的集體智慧工具包。
在這個過程中,你將使用多個 API 和開源工具包,包括使用 Lucene 進行文本分析和搜索、使用 Nutch 進行網路爬蟲,以及使用 WEKA 和 Java 數據挖掘 (JDM) 標準應用機器學習演算法。
