collaborative filtering是什麼意思，collaborative filtering的意思翻譯、用法、同義詞、例句

協同過濾；協作篩選

Result shows that the proved algorithm can be more effective and accurate than traditional collaborative filtering algorithms for new user by contrastive experiment.

為了提高新用戶服務的預測準确率，提出一種融合多系統用戶信息的協同過濾算法。

Collaborative filtering is becoming a popular one, but traditional collaborative filtering algorithm has the problem of sparsity, which will influence the efficiency of prediction.

協作過濾作為其中一種技術也得到迅速發展，但傳統的協作過濾算法存在矩陣稀疏性等問題，影響預測效果。

Today, five approaches are used by recommender systems to generate recommendations, namely knowledge engineering, collaborative filtering, content-based, hybrid and data mine approaches.

推薦方法包括：知識工程、基于内容的推薦方法、協同過濾推薦方法、混合推薦方法、數據挖掘方法。

In order to evaluate our new collaborative filtering algorithm and combined approach, we have developed a Prototype System for Chinese computer science literature automatic filtering.

為了對我們提出的改進的協作過濾算法和結合過濾方法進行評價，我們研制了一個中文計算機科技文獻自動過濾原型系統。

The collaborative filtering for the personalized recommendation is by far the most widely used and the most successful personalized recommender technology.

其中，個性化推薦系統中的協同過濾推薦是迄今為止應用最廣泛、最成功的推薦技術。

Traditional collaborative filtering does little or no offline computation, and its online computation scales with the number of customers and catalog items.

傳統的協同過濾隻做很少或不做離線計算，其線上計算量取決于顧客和登記在冊商品的數量。

Unlike traditional collaborative filtering, our algorithm's online computation scales independently of the number of customers and number of items in the product catalog.

與傳統的協同過濾，我們的算法的線上計算尺度，獨立的客戶數量和産品目錄中的項目數。

This model of collaborative filtering technology is great help in the mitigation of existing sparse problems and recommendation in time.

該模型的建立對于緩解協同過濾技術中存在的稀疏性問題、推薦的實時性問題有很大的幫助。

Unlike other algorithms, item-to-item collaborative filtering is able to meet this challenge.

與其他算法不同，商品到商品的協同過濾能滿足這樣的挑戰。

A traditional collaborative filtering algorithm represents a customer as an N-dimensional vector of items, where N is the number of distinct catalog items.

傳統的協同過濾算法把顧客描繪成商品的N維向量，其中N是登記在冊的不同商品的數量。

Thus, this study focused on the collaborative filtering technology.

本文主要針對協同過濾推薦技術展開研究。

Collaborative Filtering(CF) is used for forming recommendation by analyzing the common taste shared by a group of customers.

協同過濾技術可以通過分析客戶群共同的消費品味來形成推薦。

The traditional Collaborative Filtering has shortcoming as follows: accuracy, data sparse and cold-start.

傳統的協同過濾主要存在着：精确性、數據稀疏與冷啟動的問題。

Collaborative filtering recommendation algorithm can make choices based on the opinions of other people. It is the most successful technology for building recommender systems to date.

協同過濾是目前最成功的一種推薦算法，它能夠基于其他用戶的觀點幫助人們作出選擇。

Our algorithm, item-to-item collaborative filtering, scales to massive data sets and produces high-quality recommendations in real time.

我們的算法，也就是商品到商品的協同過濾，符合海量的數據集和産品量，并能實時得到高品質的推薦。

Unfortunately, traditional collaborative filtering algorithm does not consider the problem of item's multiple contents and often leads to bad recommendation when item has multiple contents.

但由于傳統的協同過濾算法沒有考慮項目多内容問題，存在項目多内容情況時推薦質量較差。

As you can see from above, it is certainly possible to have a good collaborative filtering system without a recommendation engine (as seen in Flickr).

正如你從上述中所看到的，如果沒有一個推薦引擎（如看到的Flickr ）這當然也有可能是一個良好的協同過濾系統。

Regardless of the method, collaborative filtering or inherent properties of things - recommendations are an unforgiving business, where false positives quickly turn users off.

不管用什麼方法，協同過濾或基于item相似的推薦都是不會被原諒的商業工具，假陽性般的錯誤會很快地讓用戶流失。

Collaborative filtering is one of the most widely used and successful methods for recommendation, which has been made fast development in theoretical research and applications.

協同過濾技術是推薦系統中最廣泛使用和最成功的技術之一，在理論研究和實踐中都取得了快速的發展。

There are three common personalized recommendatory technologies: information retrieval and extractor, content-based filtering and collaborative filtering, data mining and knowledge discovery.

常用的個性化服務推薦技術包括三種：信息檢索與信息抽取、基于内容的過濾和協同過濾、數據挖掘與知識發現。

Recommendation Subsystem is core of the whole system, which implements thesaurus concept hierarchy collaborative filtering algorithm by several steps.

其中資源推薦子系統作為整個系統的核心，主要負責本實驗系統中主題詞概念分層協同過濾推薦算法的實現。

The key to item-to-item collaborative filtering's scalability and performance is that it creates the expensive similar-items table offline.

商品到商品協同過濾的可擴展性和性能的關鍵是，它離線建立耗時巨大的相似商品表格。

Google also wanted to leverage the same collaborative filtering technology to be able to recommend images, videos, and music, for which it's more difficult to analyze the underlying content.

Google希望能夠通過調節這個複合篩選技術來解決内容分析方法難以解決的圖片，video，還有音樂方面的推薦。

They do so using a technique called collaborative filtering, basing suggestions on customers’ previous purchases and on how they rate products compared to other consumers.

他們長期向委托人推薦産品和電影影音軟件，并且用一種叫做協同過濾（一種建立在特定消費者之前消費行為以及他們對商品排序基礎上的主流技術方法）的手段，基于顧客之前購買商品時提出的建議以及顧客對商品的評價同其他顧客對比情況進行銷售。

The key point to grasp about collaborative-filtering software is that it knows absolutely nothing about movies.

對于“協同篩選”軟件，把握的關鍵點在于它對電影一無所知。

A less obvious means of Web personalization is collaborative-filtering software that resides on a Web site and tracks users' movements.

另一個不太引人注意的網站個人化的手段是協作過濾軟件，它駐留在網站中，跟蹤用戶動向。

Realize the clustering algorithm part of the recommendation system based on collaborative filtering and evaluate it.

對基于聚類的協同過濾推薦系統的聚類算法進行了實現和評價。