[1]崔婉秋,杜军平,周南,等.基于用户意图理解的社交网络跨媒体搜索与挖掘[J].智能系统学报,2017,12(6):761-769.[doi:10.11992/tis.201706075]
CUI Wanqiu,DU Junping,ZHOU Nan,et al.Social network cross-media searching and mining based on user intention[J].CAAI Transactions on Intelligent Systems,2017,12(6):761-769.[doi:10.11992/tis.201706075]
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CUI Wanqiu,DU Junping,ZHOU Nan,et al.Social network cross-media searching and mining based on user intention[J].CAAI Transactions on Intelligent Systems,2017,12(6):761-769.[doi:10.11992/tis.201706075]
基于用户意图理解的社交网络跨媒体搜索与挖掘
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
12
期数:
2017年第6期
页码:
761-769
栏目:
综述
出版日期:
2017-12-25
- Title:
- Social network cross-media searching and mining based on user intention
- Keywords:
- online social network; user searching intention; knowledge graph; deep semantic learning; precise searching
- 分类号:
- TP393
- 摘要:
- 随着在线社交网络的盛行，网络用户不仅对信息资讯的获取速度和实时性提出了更高的要求，对个性化和精确化的搜索需求日益增长。为了提升搜索引擎的质量以及其结果列表的准确性，需要深层次地挖掘用户搜索意图。本文分析了用户搜索意图理解在线社交网络跨媒体进行精准搜索与挖掘的研究现状，包括知识图谱在线社交网络多模态信息感知、面向用户搜索意图匹配的跨媒体大数据深度语义学习方面的应用，以及用户搜索意图理解的在线社交网络精准搜索与挖掘的应用等。最后，对未来研究存在的问题和可能面临的挑战进行了展望。
- Abstract:
- With the popularity of online social networks, users not only have higher requirements for speed and real-time performance of information acquisition but also increased demand for personalized and accurate searching. To improve the quality of the search engine and accuracy of the result list, it is necessary to deeply mine the search intentions of the users. This paper summarizes the current situation in precise cross-media searching and mining based on user search intentions. We focus on multi-modal information perceptions based on an online social network knowledge graph, deep semantic learning and analysis of cross-media data for user search intention matching, and precise online social network searching and mining based on users’ search intentions. Finally, future research problems and possible challenges are discussed.
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备注/Memo
收稿日期:2017-06-22;改回日期:。
基金项目:国家自然科学基金重点项目（61532006）；国家自然科学基金国际合作项目（61320106006）；国家自然科学基金青年科学基金项目（61502042）.
作者简介:崔婉秋,女,1990年生,博士研究生,主要研究方向为社交网络分析、机器学习、信息检索;杜军平,女,1963年生,教授,博士生导师,主要研究方向为人工智能、社交网络分析、数据挖掘、运动图像处理,主持国家“863”、“973”计划项目、国家自然科学基金重点项目、国家自然科学基金重大国际合作项目、北京市自然科学基金重点项目等;周南,男,1991年生,博士研究生,主要研究方向为社交网络分析、机器学习、信息检索。
通讯作者:杜军平.E-mail:junpingdu@126.com.
更新日期/Last Update:
2018-01-03