Tag's Depth-Based Expert Profiling Using a Topic Modeling Technique

Kichou Saida; Boussaid Omar; Meziane Abdelkrim

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Tag's Depth-Based Expert Profiling Using a Topic Modeling Technique

机译：标签的基于深度的专家分析，使用主题建模技术

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Expert finding and expert profiling are two important tasks for organizations, researchers, and work seekers. This importance can also be seen in online communities especially with the explosion of social networks. Expert finding on one hand addresses the task of finding the right person with the appropriate knowledge or skills. Expert profiling on the other hand gives a concise and meaningful description of a candidate expert. This paper focuses on what social tagging can bring to improve expert finding and profiling. A novel expertise indicator that models and assesses an expert based on the expert's tagging activities is proposed. First, tags are used as interest indicator to build candidate's profiles; then, Latent Dirichlet Allocation algorithm (LDA) is used to construct the tags distribution over topics by exploiting the tag's semantic characteristics. Topics of interest are then filtered using tag's depth. The latter is finally used as the expertise indicator. Experiments performed on the stack overflow dataset show the accuracy of the proposed approach.

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来源
《International journal on Semantic Web and information systems》 |2020年第4期|共19页
作者
Kichou Saida; Boussaid Omar; Meziane Abdelkrim;
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作者单位

Bejaia Univ Exact Sci Fac Comp Sci Dept Bejaia Algeria;

Lyon Univ ERIC Lab Lyon France;

Res Ctr Sci &

Tech Informat CERIST Algiers Algeria;

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原文格式 PDF
正文语种 eng
中图分类计算机网络;
关键词
Expert Profiling; Expertise; Finding; Folksonomy; Information Retrieval; LDA; Personomy; Social Tagging; Tags; Topic Modeling;

机译：专业分析;专业知识;发现;愚蠢;信息检索;LDA;人物;社交标记;标签;主题建模;

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3. Identification of Topics from Scientific Papers through Topic Modeling [J] . Denis Luiz Marcello Owa 应用科学（英文） . 2021,第004期
4. TOPIC SPLITTING: A HIERARCHICAL TOPIC MODEL BASED ON NON-NEGATIVE MATRIX FACTORIZATION [J] . Rui Liu, Xingguang Wang, Deqing Wang, 系统科学与系统工程学报（英文版） . 2018,第004期
5. Combining paper cooperative network and topic model for expert topic analysis and extraction [J] . Gao Shengxiang, Li Xian, Yu Zhengtao, Neurocomputing . 2017,第sepa27期

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6. Expert Detection and Recommendation Model With User-Generated Tags in Collaborative Tagging Systems [J] . Mengmeng Shen, Jun Wang, Ou Liu, Journal of database management . 2020,第4期

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7. Modeling Topic and Community Structure in Social Tagging: the TTR-LDA-Community Model [J] . Daifeng Li, Ying Ding, Cassidy Sugimoto, Journal of the American Society for Information Science and Technology . 2011,第9期

机译：社会标签中的主题和社区结构建模：TTR-LDA-社区模型
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机译：通过主题建模创建POS标记和依赖解析专家
9. Topic models for tagged text. [D] . Ma, Zhiqiang. 2014

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10. Sequence-tagged microsatellite profiling (STMP): a rapid technique for developing SSR markers [O] . M. J. Hayden, P. J. Sharp 2001

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12. K-Means Subject Matter Expert Refined Topic Model Methodology. [R] . Parker, N., Allen, T. T., Sui, Z. 2017

机译：K-means主题专家精炼主题模型方法论。

Tag's Depth-Based Expert Profiling Using a Topic Modeling Technique

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