Adaptive On-Line Web Topic Detection Method for Web News Recommendation System

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Adaptive On-Line Web Topic Detection Method for Web News Recommendation System

更新时间：2025-07-08

- Adaptive On-Line Web Topic Detection Method for Web News Recommendation System
- Acta Electronica Sinica Vol. 38, Issue 11, Pages: 2620-2624(2010)
- 作者机构：
  
  1. 哈尔滨工业大学计算机科学与技术学院,黑龙江,哈尔滨,150001
  2. 哈尔滨工业大学深圳研究生院,深圳市网络环境智能计算重点实验室,广东,深圳,518055
  3. 哈尔滨工业大学计算机科学与技术学院黑龙江哈尔滨,150001
  4. 哈尔滨工业大学深圳研究生院深圳市网络环境智能计算重点实验室广东深圳,518055
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Published：2010
- 稿件说明：
移动端阅览
Adaptive On-Line Web Topic Detection Method for Web News Recommendation System[J]. Acta Electronica Sinica, 2010, 38(11): 2620-2624.
DOI：

Adaptive On-Line Web Topic Detection Method for Web News Recommendation System[J]. Acta Electronica Sinica, 2010, 38(11): 2620-2624. DOI：

摘要

本文提出了一种基于改进HotRank算法的站点排序及种子URL选择方法

建立了在线主题发现系统信息采集自适应增量更新模型;结合LDA模型和仿射传播聚类算法(AP)

提出了一种网络主题发现和热点新闻推荐方法

并在海天园知识服务平台热点新闻推荐系统中得到了应用.

Abstract

We put forward a new URL choosing method and an incremental refreshing model based on HotRank algorithm.Using this method

the adaptive incremental refreshing model for hot news recommendation system is developed.A new topic detection and topic based hot news recommendation algorithm is proposed combining LDA and Affinity Propagation(AP).This research supports the development of hot news recommendation system

which is an important part of Haitianyuan knowledge service platform.

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