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1.
[目的/意义]在社会化问答社区,如何留住用户,促进用户的持续答题一直是人们关注的焦点。[方法/过程]根据社会交换理论,构建社区涉入、群体规范、效益导向快速关系、约束导向快速关系、问答满意度及持续答题意愿之间的影响关系模型,通过调查问卷收集数据,利用SPSS和AMOS进行统计分析和假设检验。[结果/结论]研究结果表明,效益导向快速关系和约束导向快速关系对问答满意度、持续答题意愿都有显著的正向影响,问答满意度在“快速关系→问答满意度→持续答题意愿”路径中起部分中介作用,社区涉入和群体规范能够促进效益导向与约束导向快速关系的建立。 相似文献
2.
The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities. 相似文献
3.
The purpose of the current study is to identify the user criteria and data-driven features, both textual and non-textual, for assessing the quality of answers posted on social questioning and answering sites (social Q&A) across four different knowledge domains—Science, Technology, Art and Recreation. A comprehensive review of literature on quality assessment of information produced in social contexts was carried out to develop the theoretical framework for the current study. A total of 23 user criteria and 24 data features were proposed and tested with high-quality answers obtained from four social Q&A sites in Stack Exchange. Findings indicate that content-related criteria and user and review features were the most frequently used in quality assessments, while the importance of user criteria and data features was variable across the knowledge domains. In the Technology Q&A site containing mostly self-help questions, the utility class was the most frequently used group of criteria. The popularity of the socio-emotional class was more apparent in discussion-oriented topic categories such as Art and Recreation, where people seek others’ opinions or advice. Users of Art and Recreation Q&A sites in Stack Exchange appear to place more value on answerers’ efforts and time, good attitudes or manners, personal experience, and the same taste. The importance of user features and the emphasis on answerer's expertise on the Science Q&A site was observed. Examining the connection or gap between user quality criteria and data features across the knowledge domains could help to better understand users’ evaluation behaviors for their preferred answers, and identify the potential of social Q&A for user education/intervention in answer quality evaluation. This examination also offers practical guidance for designing more effective social Q&A platforms, considering how to customize community support systems, motivate contributions, and control content quality. 相似文献
4.
《Information processing & management》2023,60(2):103207
Visual Question Answering (VQA) requires reasoning about the visually-grounded relations in the image and question context. A crucial aspect of solving complex questions is reliable multi-hop reasoning, i.e., dynamically learning the interplay between visual entities in each step. In this paper, we investigate the potential of the reasoning graph network on multi-hop reasoning questions, especially over 3 “hops.” We call this model QMRGT: A Question-Guided Multi-hop Reasoning Graph Network. It constructs a cross-modal interaction module (CIM) and a multi-hop reasoning graph network (MRGT) and infers an answer by dynamically updating the inter-associated instruction between two modalities. Our graph reasoning module can apply to any multi-modal model. The experiments on VQA 2.0 and GQA (in fully supervised and O.O.D settings) datasets show that both QMRGT and pre-training V&L models+MRGT lead to improvement on visual question answering tasks. Graph-based multi-hop reasoning provides an effective signal for the visual question answering challenge, both for the O.O.D and high-level reasoning questions. 相似文献
5.
Wanpeng Song Liu Wenyin Naijie Gu Xiaojun Quan Tianyong Hao 《Information processing & management》2011
Question categorization, which suggests one of a set of predefined categories to a user’s question according to the question’s topic or content, is a useful technique in user-interactive question answering systems. In this paper, we propose an automatic method for question categorization in a user-interactive question answering system. This method includes four steps: feature space construction, topic-wise words identification and weighting, semantic mapping, and similarity calculation. We firstly construct the feature space based on all accumulated questions and calculate the feature vector of each predefined category which contains certain accumulated questions. When a new question is posted, the semantic pattern of the question is used to identify and weigh the important words of the question. After that, the question is semantically mapped into the constructed feature space to enrich its representation. Finally, the similarity between the question and each category is calculated based on their feature vectors. The category with the highest similarity is assigned to the question. The experimental results show that our proposed method achieves good categorization precision and outperforms the traditional categorization methods on the selected test questions. 相似文献
6.
This paper describes how questions can be characterized for question answering (QA) along different facets and focuses on questions that cannot be answered directly but can be divided into simpler ones so that they can be answered directly using existing QA capabilities. Since individual answers are composed to generate the final answer, we call this process as compositional QA. The goal of the proposed QA method is to answer a composite question by dividing it into atomic ones, instead of developing an entirely new method tailored for the new question type. A question is analyzed automatically to determine its class, and its sub-questions are sent to the relevant QA modules. Answers returned from the individual QA modules are composed based on the predetermined plan corresponding to the question type. The experimental results based on 615 questions show that the compositional QA approach outperforms the simple routing method by about 17%. Considering 115 composite questions only, the F-score was almost tripled from the baseline. 相似文献
7.
Question answering websites are becoming an ever more popular knowledge sharing platform. On such websites, people may ask any type of question and then wait for someone else to answer the question. However, in this manner, askers may not obtain correct answers from appropriate experts. Recently, various approaches have been proposed to automatically find experts in question answering websites. In this paper, we propose a novel hybrid approach to effectively find experts for the category of the target question in question answering websites. Our approach considers user subject relevance, user reputation and authority of a category in finding experts. A user’s subject relevance denotes the relevance of a user’s domain knowledge to the target question. A user’s reputation is derived from the user’s historical question-answering records, while user authority is derived from link analysis. Moreover, our proposed approach has been extended to develop a question dependent approach that considers the relevance of historical questions to the target question in deriving user domain knowledge, reputation and authority. We used a dataset obtained from Yahoo! Answer Taiwan to evaluate our approach. Our experiment results show that our proposed methods outperform other conventional methods. 相似文献
8.
《Information processing & management》2020,57(4):102241
People are increasingly searching for information in social Q&A communities, especially through a new form of paid knowledge product, namely, live course. Such course provides a way for users to interact synchronously with content creators online. However, how this knowledge product is accepted and why users pay for it deserve attention from researchers. In this study, a research model was developed based on information foraging theory (IFT) and social information foraging (SIF) theory to analyze users’ information processing and evaluation when making payment decisions. Our research model was validated by collecting subjective and objective data from a Chinese social Q&A community that has been successful in offering live course services. We found that perceived quality of free content, perceived credibility of content creators, and perceived quantity of participants positively influence users’ willingness to pay, and thus, positively affects users’ payment behavior. Unexpectedly, social endorsement negatively moderates the relationship between willingness to pay and payment behavior. This study enhances the theoretical understanding of the drivers of users’ payment for live courses in social Q&A communities. For IS practice, our findings provide unique insights for community managers and content creators on how to operate paid knowledge products appropriately and effectively. 相似文献
9.
This study examines the creation of innovation-related knowledge in virtual communities visited mainly by lead users. Such communities enable firms to access a large number of lead users in a cost-efficient way. A propositional framework relates lead users’ characteristics to unique virtual community features to examine their potential impact on the development of valuable innovation knowledge. The authors empirically validate this framework by analyzing online contributions of lead users for mobile service innovation projects. The findings indicate that the value of their contributions stems from their ability to suggest solutions instead of simply describing problems or stating customer needs. Lead users’ technical expertise also makes them particularly well-suited to develop new functionalities, but less so for design and usability improvements. The digital context favors the creation of explicit knowledge that can be easily integrated into the development of new products. Finally, contributions given by lead users in a proactive way contain more novel insights than reactive contributions such as answers to community members’ questions. The findings should help managers stimulate, identify, and improve the use of lead users’ input in virtual communities. 相似文献
10.
【目的/意义】探讨网络问答社区中意见领袖的社会与知识分享行为特征,为问答社区的发展提供改进建
议。【方法/过程】以知乎“旅行”问答话题下活跃用户为研究对象,通过python爬取用户的个人信息,利用数理统计
和社会网络分析对意见领袖的社会及知识分享行为特征展开研究。【结果/结论】研究发现,社会特征是意见领袖开
展知识共享活动的先决条件,网络问答社区的发展离不开社区用户的多元化;意见领袖为问答社区内容生成主力,
知识分享行为广泛分布于意见领袖的信息活动中且其行为影响力突出;中心团体联合促进意见领袖间的知识分
享,领袖群体间知识分享互动频繁。【创新/局限】对于意见领袖的特征分析只建立在“旅行”这一问答话题,样本数
量偏低,后期将会对更多的问答话题进行研究,以期得出更精准的、普适性更强的结论。 相似文献
11.
[目的/意义]随着在线健康社区的快速发展,人们对健康问题越来越重视,并且开始关注在线健康社区中的知识共享问题。本文将S-O-R模型与动机理论结合起来,构建一个集成模型来研究在线健康社区用户的不同种类知识共享行为的影响因素。[方法/过程]本文采用问卷调查的方法收集到249份有效调查问卷,使用SPSS24.0和AMOS23.0检验所提出的假设。[结果/结论]研究结果表明,硬性报酬对利他主义和知识的自我效能均有显著正向影响,软性报酬对利他主义有正向影响,对知识的自我效能无显著正向影响。此外,利他主义对一般健康知识共享行为有显著正向影响,对特殊健康知识共享行为有显著负向影响;知识的自我效能对一般健康知识和特殊健康知识共享行为均有显著正向影响。 相似文献
12.
Question answering (QA) aims at finding exact answers to a user’s question from a large collection of documents. Most QA systems combine information retrieval with extraction techniques to identify a set of likely candidates and then utilize some ranking strategy to generate the final answers. This ranking process can be challenging, as it entails identifying the relevant answers amongst many irrelevant ones. This is more challenging in multi-strategy QA, in which multiple answering agents are used to extract answer candidates. As answer candidates come from different agents with different score distributions, how to merge answer candidates plays an important role in answer ranking. In this paper, we propose a unified probabilistic framework which combines multiple evidence to address challenges in answer ranking and answer merging. The hypotheses of the paper are that: (1) the framework effectively combines multiple evidence for identifying answer relevance and their correlation in answer ranking, (2) the framework supports answer merging on answer candidates returned by multiple extraction techniques, (3) the framework can support list questions as well as factoid questions, (4) the framework can be easily applied to a different QA system, and (5) the framework significantly improves performance of a QA system. An extensive set of experiments was done to support our hypotheses and demonstrate the effectiveness of the framework. All of the work substantially extends the preliminary research in Ko et al. (2007a). A probabilistic framework for answer selection in question answering. In: Proceedings of NAACL/HLT. 相似文献
13.
Online healthcare communities (OHCs) have become producers of medical information. Solving the issue of how to effectively reuse such a large amount of medical data and discover its potential value is of the utmost importance for alleviating the shortage of medical resources. Online consultation has received widespread attention and population since its first appearance in 1999, and as a result, many diagnostic multi-turn questions and answers (Q&A) documents have become available. This type of document is formed by multiple rounds of patient questions and doctors’ diagnostic answers and contains massive medical knowledge and doctors’ diagnostic experience. Few studies concentrate on the modeling and recommendation of this type of document, yet making these documents convenient for reuse reduces the cost of medical consultation for patients and saves time addressing common diseases for doctors. In this paper, we focus on the modeling and understanding of diagnostic multi-turn Q&A records and propose a deep-learning recommendation framework based on patient medical information needs, the contents of Q&A records and doctor background information. With the evaluation based on a real dataset that contains pediatric consultation dialogues fetched from DingXiangYuan, a famous online consultation application in China, we found that the proposed model achieved a good performance on the recommendation of diagnostic multi-turn Q&A records and outperformed baseline models. In addition, we discussed a potential application scenario of the recommendation model, suggesting that the proposed model can promote the reduction of patient costs and doctors’ work pressure in countries or regions with insufficient medical resources. 相似文献
14.
《Information processing & management》2023,60(4):103367
Many existing biomedical extractive question answering methods are based on pre-trained models, which do not take full advantage of the hidden layer knowledge of pretrained models and do not consider span overlap between answers when predicting. To address these issues, we propose a new question answering model, called ALBERT with Dynamic Routing and Answer Voting (ADRAV). The ADRAV can reasonably utilize hidden layer knowledge through dynamic routing, and consider span similarity between answers through answer voting. To improve the performance of the model, we also carry out pre-fine-tuning, and add a dynamic parameter adjustment mechanism in the process of pre-fine-tuning. Experimental results show that our model achieves significant performance improvement with fewer parameters on BioASQ 4b, 5b, 6b, 9b, and outperforms SOTA baselines on BioASQ 4b, 6b. 相似文献
15.
【目的/意义】文章对国内网络问答社区相关研究进行了考察,旨在分析其发展现状、热点主题以及未来发 展趋势,以期为该领域的深化发展提供参考。【方法/过程】主要使用了文献计量与内容归纳法对383篇期刊文献进 行了分析。【结果/结论】国内网络问答社区相关研究将继续呈指数趋势增长;所调查的期刊文献集中分布在少数学 科领域、核心期刊、核心机构中;国内网络问答社区研究可归纳为3个发展阶段,其研究主题聚焦于6个方面;未来 发展中,机构间、学者间的交互程度将进一步加强,多学科协同将成为促进领域知识体系不断完善的重要因素,知 识服务成为该领域发展的重要方向,新技术应用将驱动网络问答社区向智能化、学习化方向发展。 相似文献
16.
Community question answering (CQA) services that enable users to ask and answer questions have become popular on the internet. However, lots of new questions usually cannot be resolved by appropriate answerers effectively. To address this question routing task, in this paper, we treat it as a ranking problem and rank the potential answerers by the probability that they are able to solve the given new question. We utilize tensor model and topic model simultaneously to extract latent semantic relations among asker, question and answerer. Then, we propose a learning procedure based on the above models to get optimal ranking of answerers for new questions by optimizing the multi-class AUC (Area Under the ROC Curve). Experimental results on two real-world CQA datasets show that the proposed method is able to predict appropriate answerers for new questions and outperforms other state-of-the-art approaches. 相似文献
17.
《Information processing & management》2023,60(3):103321
Social question-and-answer (Q&A) sites have the potential to serve as a useful source of online information based on their content-focused and collaborative nature. Although previous research has examined various attributes of high-quality information on social Q&A sites (e.g., best answers), relatively less attention has been paid to what affects users’ credibility assessments of information in the social Q&A context. The present study developed a social Q&A platform-specific framework for web credibility assessment, including 21 criteria under six types of web credibility, based on a literature analysis and case study of two online Q&A communities, Stack Exchange and Wikipedia Reference Desk. Using the selected sites’ policies and guidelines (n = 46) as the source of evidence, the case study revealed that content-related attributes (e.g., evidence-based, pertinence) were most frequently identified (12 of 21 criteria) as potential cues and heuristics for web credibility assessments of social Q&A sites, followed by author-related (five of 21; e.g., reputation) and design-related (four of 21; e.g., engaging design) factors. Design-related criteria were rarely included in previous models of web credibility on social Q&A or similar peer-knowledge production platforms. However, our findings showing that both Stack Exchange and Wikipedia Reference Desk have policies regarding all four design-related criteria in our framework—engaging design, moderation, design appropriateness, and ease of use—indicate the potential influences of design features on users’ web credibility assessment on social Q&A sites. Some differences emerged between the two cases, such as policies regarding the answerer's credentials or semantic accuracy that are present on Wikipedia Reference Desk but absent on Stack Exchange. Such differences in the sites’ policies reflect how they position themselves as social Q&A communities—Wikipedia, of which Wikipedia Reference Desk is a part, as an encyclopedia, and Stack Exchange as a community-based platform for learning, sharing knowledge, and building careers of users. 相似文献
18.
Online social networking has received increasing attention as a new phenomenon among online users. As Internet users utilize online social networking websites as a useful communication tool to maintain their social networks, this study explorers online social networking websites users’ knowledge sharing in particular. This study investigated the factors which influence knowledge contribution behaviors of social networking website users by sharing through user created contents with one another. By employing a socio-technical approach, this study discussed the roles of social system factors such as ethical culture, social tie, and a sense of belonging in online social network. Additionally, this study examined technical systems factors such as structural assurance of service providers and structural assurance of the Internet. The survey method was utilized in order to empirically test the research model. The research findings and contributions are discussed as well. 相似文献
19.
《Information processing & management》2023,60(3):103296
Recent studies point out that VQA models tend to rely on the language prior in the training data to answer the questions, which prevents the VQA model from generalization on the out-of-distribution test data. To address this problem, approaches are designed to reduce the language distribution prior effect by constructing negative image–question pairs, while they cannot provide the proper visual reason for answering the question. In this paper, we present a new debiasing framework for VQA by Learning to Sample paired image–question and Prompt for given question (LSP). Specifically, we construct the negative image–question pairs with certain sampling rate to prevent the model from overly relying on the visual shortcut content. Notably, question types provide a strong hint for answering the questions. We utilize question type to constrain the sampling process for negative question–image pairs, and further learn the question type-guided prompt for better question comprehension. Extensive experiments on two public benchmarks, VQA-CP v2 and VQA v2, demonstrate that our model achieves new state-of-the-art results in overall accuracy, i.e., 61.95% and 65.26%. 相似文献
20.
Óscar Ferrández Rubén Izquierdo Sergio Ferrández José Luis Vicedo 《Information processing & management》2009
This paper presents QACID an ontology-based Question Answering system applied to the CInema Domain. This system allows users to retrieve information from formal ontologies by using as input queries formulated in natural language. The original characteristic of QACID is the strategy used to fill the gap between users’ expressiveness and formal knowledge representation. This approach is based on collections of user queries and offers a simple adaptability to deal with multilingual capabilities, inter-domain portability and changes in user information requirements. All these capabilities permit developing Question Answering applications for actual users. This system has been developed and tested on the Spanish language and using an ontology modelling the cinema domain. The performance level achieved enables the use of the system in real environments. 相似文献