# Expert finding and Q&A systems

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/expert-finding-and-q-and-a-systems/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the identification and retrieval of experts within online communities, particularly in the context of question answering platforms and social media. It explores various aspects such as user motivations, answer quality, relevance criteria, and techniques for routing questions to appropriate answerers. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t13274 |
| Works | 14 |

## Topic papers all

- [Accurately interpreting clickthrough data as implicit feedback](https://scholariq.org/papers/accurately-interpreting-clickthrough-data-as-implicit-feedback/)
- [Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search](https://scholariq.org/papers/evaluating-the-accuracy-of-implicit-feedback-from-clicks-and-query/)
- [Topic Modeling Using Latent Dirichlet allocation](https://scholariq.org/papers/topic-modeling-using-latent-dirichlet-allocation/)
- [The influence of task and gender on search and evaluation behavior using Google](https://scholariq.org/papers/the-influence-of-task-and-gender-on-search-and-evaluation-behavior-using-google/)
- [An Evaluation of Aggregation Techniques in Crowdsourcing](https://scholariq.org/papers/an-evaluation-of-aggregation-techniques-in-crowdsourcing/)
- [Collaborative filtering using orthogonal nonnegative matrix tri-factorization](https://scholariq.org/papers/collaborative-filtering-using-orthogonal-nonnegative-matrix-tri-factorization/)
- [Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review](https://scholariq.org/papers/analysis-of-community-question-answering-issues-via-machine-learning-and-deep/)
- [Science models as value-added services for scholarly information systems](https://scholariq.org/papers/science-models-as-value-added-services-for-scholarly-information-systems/)
- [Extending collaborative filtering recommendation using word embedding: A hybrid approach](https://scholariq.org/papers/extending-collaborative-filtering-recommendation-using-word-embedding-a-hybrid/)
- [A survey on cross-media search based on user intention understanding in social networks](https://scholariq.org/papers/a-survey-on-cross-media-search-based-on-user-intention-understanding-in-social/)
- [A comprehensive survey of techniques for developing an Arabic question answering system](https://scholariq.org/papers/a-comprehensive-survey-of-techniques-for-developing-an-arabic-question-answering/)
- [Why do master’s students of humanities and social sciences publish papers in Chinese-language predatory journals? A qualitative study based on Grounded Theory](https://scholariq.org/papers/why-do-master-s-students-of-humanities-and-social-sciences-publish-papers-in/)
- [Estimating Similarity for Grading Descriptive Handwritten Answers](https://scholariq.org/papers/estimating-similarity-for-grading-descriptive-handwritten-answers/)
- [Role-Based Resume Analysis Using Retrieval-Augmented Generation and Large Language Models](https://scholariq.org/papers/role-based-resume-analysis-using-retrieval-augmented-generation-and-large/)

## Topic primary papers

- [Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review](https://scholariq.org/papers/analysis-of-community-question-answering-issues-via-machine-learning-and-deep/)
- [Why do master’s students of humanities and social sciences publish papers in Chinese-language predatory journals? A qualitative study based on Grounded Theory](https://scholariq.org/papers/why-do-master-s-students-of-humanities-and-social-sciences-publish-papers-in/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.