共查询到20条相似文献，搜索用时 78 毫秒
1.
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
2.
3.
4.
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
5.
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
6.
【目的/意义】解决自动问答系统构建过程中数据集构建成本高的问题,以及自动问答过程中仅考虑问题或
答案本身相关性的局限。【方法/过程】提出了一种融合标注问答库和社区问答数据的数据集构建方法,构建问题关
键词-问题-答案-答案簇多层异构网络模型,并给出了基于该模型的自动问答算法。获取图书馆语料进行处理作
为实验数据,将BERT-Cos、AINN、BiMPM模型作为对比对象进行了实验与分析。【结果/结论】通过实验得到了各
模型在图书馆自动问答任务上的效果,本文所提模型在各评价指标上均优于其他模型,模型准确率达87.85%。【创
新/局限】本文提出的多数据源融合数据集构建方法和自动问答模型在问答任务中相对于已有方法具有更好的表
现,同时根据模型效果分析给出用户提问词长建议。 相似文献
7.
Alberto Téllez-Valero Manuel Montes-y-Gómez Luis Villaseñor-Pineda Anselmo Peñas Padilla 《Information processing & management》2011
Question answering (QA) is the task of automatically answering a question posed in natural language. Currently, there exists several QA approaches, and, according to recent evaluation results, most of them are complementary. That is, different systems are relevant for different kinds of questions. Somehow, this fact indicates that a pertinent combination of various systems should allow to improve the individual results. This paper focuses on this problem, namely, the selection of the correct answer from a given set of responses corresponding to different QA systems. In particular, it proposes a supervised multi-stream approach that decides about the correctness of answers based on a set of features that describe: (i) the compatibility between question and answer types, (ii) the redundancy of answers across streams, as well as (iii) the overlap and non-overlap information between the question–answer pair and the support text. Experimental results are encouraging; evaluated over a set of 190 questions in Spanish and using answers from 17 different QA systems, our multi-stream QA approach could reach an estimated QA performance of 0.74, significantly outperforming the estimated performance from the best individual system (0.53) as well as the result from best traditional multi-stream QA approach (0.60). 相似文献
8.
Bernard J. Jansen 《Information processing & management》2018,54(2):159-174
With the noted popularity of social networking sites, people increasingly rely on these social networks to address their information needs. Although social question and answering is potentially an important venue seeking information online, it, unfortunately, suffers from a problem of low response rate, with the majority of questions receiving no response. To understand why the response rate of social question and answering is low and hopefully to increase it in the future, this research analyzes extrinsic factors that may influence the response probability of questions posted on Sina Weibo. We propose 17 influential factors from 2 different perspectives: the content of the question, and the characteristics of the questioner. We also train a prediction model to forecast a question's likelihood of being responded based on the proposed features We test our predictive model on more than 60,000 real-world questions posted on Weibo, which generate more than 600,000 responses. Findings show that a Weibo's question answerability is primarily contingent on the questioner versus the question. Our findings indicate that using appreciation emojis can increase a question's response probability, whereas the use of hashtags negatively influences the chances of receiving answers. Our contribution is in providing insights for the design and development of future social question and answering tools, as well as for enhancing social network users’ collaboration in supporting social information seeking activities. 相似文献
9.
The authors of this paper investigate terms of consumers’ diabetes based on a log from the Yahoo!Answers social question and answers (Q&A) forum, ascertain characteristics and relationships among terms related to diabetes from the consumers’ perspective, and reveal users’ diabetes information seeking patterns. In this study, the log analysis method, data coding method, and visualization multiple-dimensional scaling analysis method were used for analysis. The visual analyses were conducted at two levels: terms analysis within a category and category analysis among the categories in the schema. The findings show that the average number of words per question was 128.63, the average number of sentences per question was 8.23, the average number of words per response was 254.83, and the average number of sentences per response was 16.01. There were 12 categories (Cause & Pathophysiology, Sign & Symptom, Diagnosis & Test, Organ & Body Part, Complication & Related Disease, Medication, Treatment, Education & Info Resource, Affect, Social & Culture, Lifestyle, and Nutrient) in the diabetes related schema which emerged from the data coding analysis. The analyses at the two levels show that terms and categories were clustered and patterns were revealed. Future research directions are also included. 相似文献
10.
Tolga Yilmaz Rifat Ozcan Ismail Sengor Altingovde Özgür Ulusoy 《Information processing & management》2019,56(1):228-246
Students use general web search engines as their primary source of research while trying to find answers to school-related questions. Although search engines are highly relevant for the general population, they may return results that are out of educational context. Another rising trend; social community question answering websites are the second choice for students who try to get answers from other peers online. We attempt discovering possible improvements in educational search by leveraging both of these information sources. For this purpose, we first implement a classifier for educational questions. This classifier is built by an ensemble method that employs several regular learning algorithms and retrieval based approaches that utilize external resources. We also build a query expander to facilitate classification. We further improve the classification using search engine results and obtain 83.5% accuracy. Although our work is entirely based on the Turkish language, the features could easily be mapped to other languages as well. In order to find out whether search engine ranking can be improved in the education domain using the classification model, we collect and label a set of query results retrieved from a general web search engine. We propose five ad-hoc methods to improve search ranking based on the idea that the query-document category relation is an indicator of relevance. We evaluate these methods for overall performance, varying query length and based on factoid and non-factoid queries. We show that some of the methods significantly improve the rankings in the education domain. 相似文献
11.
《Information processing & management》2023,60(2):103145
Machine reading comprehension (MRC) is a challenging task in the field of artificial intelligence. Most existing MRC works contain a semantic matching module, either explicitly or intrinsically, to determine whether a piece of context answers a question. However, there is scant work which systematically evaluates different paradigms using semantic matching in MRC. In this paper, we conduct a systematic empirical study on semantic matching. We formulate a two-stage framework which consists of a semantic matching model and a reading model, based on pre-trained language models. We compare and analyze the effectiveness and efficiency of using semantic matching modules with different setups on four types of MRC datasets. We verify that using semantic matching before a reading model improves both the effectiveness and efficiency of MRC. Compared with answering questions by extracting information from concise context, we observe that semantic matching yields more improvements for answering questions with noisy and adversarial context. Matching coarse-grained context to questions, e.g., paragraphs, is more effective than matching fine-grained context, e.g., sentences and spans. We also find that semantic matching is helpful for answering who/where/when/what/how/which questions, whereas it decreases the MRC performance on why questions. This may imply that semantic matching helps to answer a question whose necessary information can be retrieved from a single sentence. The above observations demonstrate the advantages and disadvantages of using semantic matching in different scenarios. 相似文献
12.
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
13.
课堂教学的方法中,提问法是一种常用的方法．通常是老师负责提问,学生负责回答,因此也称为问答法。提问的目的在于使学生思维得到开发,能够真正对知识融会贯通。在初中的数学教学中,提问法经常被使用．而老师提问的技巧也多种多样,例如趣味提问法、发散提问法、悬念提问法以及铺垫提问法等等,因此本文通过对初中数学教学中的提问技巧进行分析,从而找出能够促进学生思维发展的提问方法． 相似文献
14.
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
15.
《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
16.
17.
Recently, question series have become one focus of research in question answering. These series are comprised of individual factoid, list, and “other” questions organized around a central topic, and represent abstractions of user–system dialogs. Existing evaluation methodologies have yet to catch up with this richer task model, as they fail to take into account contextual dependencies and different user behaviors. This paper presents a novel simulation-based methodology for evaluating answers to question series that addresses some of these shortcomings. Using this methodology, we examine two different behavior models: a “QA-styled” user and an “IR-styled” user. Results suggest that an off-the-shelf document retrieval system is competitive with state-of-the-art QA systems in this task. Advantages and limitations of evaluations based on user simulations are also discussed. 相似文献
18.
Alaa Mohasseb Mohamed Bader-El-Den Mihaela Cocea 《Information processing & management》2018,54(6):1228-1243
Question-answering has become one of the most popular information retrieval applications. Despite that most question-answering systems try to improve the user experience and the technology used in finding relevant results, many difficulties are still faced because of the continuous increase in the amount of web content. Questions Classification (QC) plays an important role in question-answering systems, with one of the major tasks in the enhancement of the classification process being the identification of questions types. A broad range of QC approaches has been proposed with the aim of helping to find a solution for the classification problems; most of these are approaches based on bag-of-words or dictionaries. In this research, we present an analysis of the different type of questions based on their grammatical structure. We identify different patterns and use machine learning algorithms to classify them. A framework is proposed for question classification using a grammar-based approach (GQCC) which exploits the structure of the questions. Our findings indicate that using syntactic categories related to different domain-specific types of Common Nouns, Numeral Numbers and Proper Nouns enable the machine learning algorithms to better differentiate between different question types. The paper presents a wide range of experiments the results show that the GQCC using J48 classifier has outperformed other classification methods with 90.1% accuracy. 相似文献
19.
Answer selection is the most complex phase of a question answering (QA) system. To solve this task, typical approaches use unsupervised methods such as computing the similarity between query and answer, optionally exploiting advanced syntactic, semantic or logic representations. 相似文献
20.
This paper presents a roadmap of current promising research tracks in question answering with a focus on knowledge acquisition and reasoning. We show that many current techniques developed in the frame of text mining and natural language processing are ready to be integrated in question answering search systems. Their integration opens new avenues of research for factual answer finding and for advanced question answering. Advanced question answering refers to a situation where an understanding of the meaning of the question and the information source together with techniques for answer fusion and generation are needed. 相似文献