Personalized Mobile Searching Approach Based on Combining Content-Based Filtering and Collaborative Filtering
Personalized Mobile Searching Approach Based on Combining Content-Based Filtering and Collaborative Filtering
复制标题
基于内容过滤和协同过滤相结合的个性化移动搜索方法
DOI：
10.1109/jsyst.2015.2472996
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发表时间：
2017-03-01
影响因子：
4.4
通讯作者：
Yu, Chen
中科院分区：
文献类型：
--
作者：
Zhao, Feng;Yan, Fengwei;Yu, Chen
Amazon、Google AppEngine、Microsoft Azure等云计算平台上的资源，很好地弥补了移动的设备本地资源的不足，为移动的搜索开辟了新的空间，提高了云资源的可用性。从本质上讲，移动的搜索是一种上下文感知和个性化的活动，因为移动的设备固有的可移动性允许人们随时随地检索信息。然而，当前的移动的搜索产品总是远离个性化，并且以移动的平台的融合为中心的准确性。针对个性化移动的搜索，提出了一种基于内容过滤和协同过滤相结合的混合过滤机制，以消除不相关或不太相关的搜索结果。前者根据从用户的查询历史生成的移动的用户的特征模型过滤结果，后者使用从用户的通信历史构造的用户的社交网络过滤结果。实验表明，该过滤机制可以显著提高用户在移动的手机上的个性化和精确搜索体验。
Resources in cloud computing platforms such as Amazon, Google AppEngine, and Microsoft Azure are a natural fit to remedy the lack of local resources in mobile devices, which creates a new space of mobile search to improve the availability of cloud resources. In essence, mobile search is a context-aware and personalized activity since mobile devices' inherent movability allows people to retrieve information anytime and anywhere. However, current mobile search products are always far from personalized and are accuracy centered on the convergence of mobile platforms. In this paper, a hybrid filtering mechanism is proposed to eliminate irrelevant or less relevant results for personalized mobile search, which combines content-based filtering and collaborative filtering. The former filters the results according to the mobile user's feature model generated from the user's query history, and the latter filters the results using the user's social network, which is constructed from the user's communication history. Experiments show that the filtering mechanism can significantly improve the user's personalized and precise searching experience on mobile phones.