共查询到20条相似文献，搜索用时 191 毫秒
1.
《Knowledge Acquisition》1993,5(1):37-77
To make plan-based expert systems more accessible to end users and to support user tasks effectively, we present a system that makes the functionality of AI-planning techniques seem natural and immediately understandable. In particular, we present a task support system with a graphical interaction language for the acquisition and display of plan knowledge, where the intended users are domain experts and novices and where previous computer literacy is not required. Based on existing theories in cognitive science and on our own experimental research, we propose a cognitive model of the users' view of tasks. The model postulates the domain experts' ability to recall relevant parts of self-performed tasks in the application domain. The validity of the model is demonstrated in a paper-and-pencil experiment.Employing a cognitive systems engineering approach, we use the cognitive model, a stage process model of knowledge acquisition, and requirements from the plan formalism to specify DACRON, a system for plan acquisition and task support. DACRON supports the acquisition of plan knowledge by providing graphical representations of domain entities from the users' point of view. DACRON checks the consistency of specified units and graphically aids the debugging process. DACRON also allows the animated presentation of the planning process and its results. To evaluate the usability of DACRON and the relevance of the acquired and displayed knowledge in application domains, experimental studies involving 39 users were conducted. The studies show that over 90% of the subjects could easily use DACRON to enter knowledge, and 80% of the entered knowledge was relevant and correct. In the case of knowledge display, subjects were able to use the displayed knowledge effortlessly and apply it to solve 95% of the domain problems presented. 相似文献
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web中大量新闻网页、博客、电子邮件等非结构化信息中蕴含着大量的知识,对其进行处理以自动获得知识具有重要意义。目前,一些基于信息抽取等技术抽取简单关联关系的知识获取应用系统存在明显的局限性,本文引入Apache Stanbol——Apache下的一种从非结构化信息中自动获取知识的开源项目,它是一个为语义内容管理设计的模块化的软件集和可重用组件,旨在将传统内容管理系统（CMS）拓展为支持语义服务的语义内容管理系统（SCMS）,在此基础上,为改善搜索引擎关于内容的搜索、分类,实体消歧及语义化查询等带来帮助。 相似文献
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域分析与情报检索理论 总被引：1，自引：0，他引：1
域分析与情报检索理论王知津ＡＢＳＴＲＡＣＴＴｈｅａｕｔｈｏｒｄｉｓｃｕｓｓｅｓｄｏｍａｉｎａｎａｌｙｓｉｓ，ａｎｅｗｍｅｔｈｏｄｉｎｉｎｆｏｒｍａｔｉｏｎｓｃｉｅｎｃｅｆｏｃｕｓｉｎｇｏｎｔｈｅａｎａｌｙｓｉｓｏｆｄｏｍａｉｎｋｎｏｗｌｅｄｇｅ．Ｍｅ... 相似文献
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Eileen Wood Domenica De Pasquale Julie Lynn Mueller Karin Archer Lucia Zivcakova Kathleen Walkey 《The Reference Librarian》2013,54(3):182-204
The relative contributions of expertise in search skills and domain knowledge were examined when using the Internet to find information. Four conditions were compared: expert searchers/high domain knowledge; expert searchers/low domain knowledge; novice searchers/high domain knowledge; and novice searchers/low domain knowledge. Search outcomes and verbal protocols were analyzed. The combination of search expertise and high domain knowledge yielded the most efficient searches. Higher search expertise yielded access to sites rated more accurate and credible. High domain knowledge yielded sites rated more thorough. Verbal protocols depicted searching as a complex decision process. Findings have implications for instructional support. 相似文献
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In this paper, we present a framework that can process a user query for retrieval of information from documents of different properties across multiple domains, with specific application to patent laws and regulations. The framework has three basic components. The first component is ontology mapping and generation. What happens is that the keywords entered by users are mapped into a subset of relevant keywords. This step is performed by looking up those words in an ontology database. The second component is the joint and cross search in various document domains; in our case, they are patents and scientific publications. The last component is to modify the search results by applying user feedback statistics. The results of feedback will be saved as metadata for future uses.A case example is given to demonstrate how results from multiple domain searches can be combined using ontology and cross referencing. We use an example of well-known biotechnology patents on erythropoietin (EPO) and give detailed analysis on each document domain with this keyword. Relationships between each domain are demonstrated.A user feedback mechanism is also discussed in this paper. The ability to take user feedback into the framework is important. There is no doubt that domain knowledge from expert or experienced users could be a very good compliment to the proposed system. Both direct and indirect user feedbacks are discussed. 相似文献
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[目的/意义] 构建基于关联数据的探索式检索系统,充分利用关联数据中隐藏的知识网络,向用户提供发现新知识的机会。[方法/过程] 基于DBpedia电影数据集,采用改进的向量空间模型进行关联数据的语义相似度计算,使用可视化的交互技术对检索结果进行呈现。[结果/结论] 通过基于任务的评价方法与IMDB进行对比,证明基于关联数据的探索式检索系统能够提高检索效率,提升用户体验并能引导用户发现其感兴趣的信息。 相似文献
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Dustin Hillard Eren Manavoglu Hema Raghavan Chris Leggetter Erick Cantú-Paz Rukmini Iyer 《Information Retrieval》2011,14(3):315-336
The critical task of predicting clicks on search advertisements is typically addressed by learning from historical click data.
When enough history is observed for a given query-ad pair, future clicks can be accurately modeled. However, based on the
empirical distribution of queries, sufficient historical information is unavailable for many query-ad pairs. The sparsity
of data for new and rare queries makes it difficult to accurately estimate clicks for a significant portion of typical search
engine traffic. In this paper we provide analysis to motivate modeling approaches that can reduce the sparsity of the large
space of user search queries. We then propose methods to improve click and relevance models for sponsored search by mining
click behavior for partial user queries. We aggregate click history for individual query words, as well as for phrases extracted
with a CRF model. The new models show significant improvement in clicks and revenue compared to state-of-the-art baselines
trained on several months of query logs. Results are reported on live traffic of a commercial search engine, in addition to
results from offline evaluation. 相似文献
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针对现有元数据索引方法因其固有的缺陷而难以应用于复杂的语义网络,提出一种新的基于语义的元数
据索引查询方法。该方法以ＲＤＦ图为数据模型,在路径索引的基础上,为元数据建立索引,并通过路径表达式实现元数据的查询。它能有效的促进领域知识的共享和语义表达,提高元数据的检索效率和查准率,为用户和应用提供语义查询和信息汇集能力。 相似文献
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互联网思维下图书馆服务变革探讨 总被引：8，自引：2，他引：6
[目的/意义]互联网颠覆了物质世界的思维基础,引发的改变是观念,对图书馆服务的思考必须转变为互联网思维这一重要思考方式。[方法/过程]梳理互联网思维产生的背景、概念,总结互联网思维特征,论述其对图书馆服务的意义及其对图书馆服务的影响。提出改变观念,深度解读用户;免费开放,促进信息公平;以数字化形式,实现用户的普遍获取;以信息专家的角色,嵌入用户过程;借力新媒体,提供方便、快捷的服务等图书馆服务理念。[结果/结论]应从变革思维、与虚拟空间相连接、营销推广图书馆服务、发挥技术驱动作用4个方面拓展图书馆服务的互联网思维。以数字化、网络为基础,围绕用户需求,把用户体验做到极致,以期推动图书馆服务创新发展。 相似文献
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[目的/意义]研究网络环境中学术用户的探索式搜索行为特征,设计专业的信息服务策略,帮助馆员精准定位用户需求,提高服务的准确率。[研究设计/方法]以探索式信息搜索的3个不确定性为核心,整合探索式搜索行为的知识构建、问题情境与认知阶段,分析用户的领域知识和搜索技能对探索式搜索行为的影响。[结论/发现]根据先验知识集合将学术用户分为4种类型,结合用户搜索过程中的不确定种类与认知阶段,分别提供基础型、辅助型、辅导型和专业型服务。[创新/价值]围绕探索式搜索行为的不确定性,提出探索式搜索行为的认知过程框架及分类型分阶段信息服务策略。 相似文献
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[目的/意义]了解、分析和识别用户学术搜索时所表达的信息需求是优化查询结果、提高学术搜索引擎用户体验的首要步骤,而用户进行学术搜索时通过查询表达式所表达的用户表意信息需求及潜在信息需求可称之为学术查询意图。本文总结学术查询意图类目体系有助于学术查询意图识别和检索结果页面的呈现。[方法/过程]在A.Broder的查询意图类目体系的基础上,结合百度学术搜索查询日志中查询表达式实例,构建学术查询意图的类目体系。以此为基础,总结不同类别的学术查询意图,并分析不同类别学术查询意图下查询表达式的特点。[结果/结论]学术查询意图主要分为学术文献类、学术实体类、学术探索类、知识问答类和非学术文献类五大类;得出不同类别学术查询意图在学术搜索中的大致比例;给出每类学术查询意图的查询表达式特征、查询情景和查询结果页。 相似文献
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认知建构视角下交互式信息检索模型研究 总被引：1，自引：0，他引：1
[目的/意义]信息检索本质上是一个认知过程,研究促进用户认知的交互式信息检索模型具有重要意义。[研究设计/方法]以建构主义理论为指导,以促进用户的认知发展为研究目标,构建了以信息空间层、用户空间层和界面交互层为顶层分析框架的交互式信息检索模型,并开发了原型系统。[结论/发现]实验结果表明原型系统能有效地促进用户对信息空间的探索与挖掘,帮助用户积极主动地进行认知建构,发展认知空间。[创新/价值]将认知建构理论运用于信息检索领域,从交互设计方面对检索系统提出了改进建议,以更好地提供认知支持。 相似文献
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基于个体概念语义关系的微内容发现研究 总被引：1，自引：0，他引：1
传统的超文本标记语言只能显示而不能使计算机理解页面信息,导致传统的基于关键词的检索工具的查准率、查全率和智能化程度都较低.虽然语义网可以解决计算机对页面信息的理解问题,但以往基于本体的语义匹配算法通常是面向类概念的,在精度上不能满足微内容的发现需求.本文面向微内容检索应用,在分析了个体概念的语义特征的基础上,提出了基于语义关系的个体匹配规则、索引结构和相应的语义检索算法.最后,通过实验验证,证明了基于个体语义关系的聚合机制具有更高的聚合细腻度,所提出的语义检索算法在面向微内容的检索应用中是有效的. 相似文献
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将稀缺理论与用户认知理论结合,可以重新定义用户在信息检索过程中的认知行为,合理地阐明用户认知行为的发展趋势,提升信息检索研究的有效性与科学性。本文研究分析了稀缺心理对用户认知的动态影响过程,并在稀缺心理的基础上解释了用户潜在信息需求的深层原因。实验结果证明了用户的社交网络行为与信息检索行为之间存在一定的语义关系,通过提取用户社交网络数据,为研究用户个性化需求提供理论依据和参考依据,有利于信息检索个性化服务的实现。 相似文献
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《Knowledge Acquisition》1994,6(4):343-367
This paper presents a knowledge-based software engineering tool, DASERT (Detection of Anomalies in Software Engineering Requirements Texts), to acquire and validate functional requirements in natural language. The user describes the functional specifications through informal methods, using graphics with comments in natural language. During this elaboration step the system validates the document by processing the comments semantically to detect ambiguities or inconsistencies. To do so it uses natural language processing and knowledge base engineering.DASERT's kernel is a KL-ONE-like semantic network, which helps the semantic parsing of the comments and their semantic representation. This knowledge base is first initialized by the acquisition of the lexical domain knowledge, then progressively enriched with the domain terminology given by the user and with the requirements knowledge extracted from the user's graphics and texts.During initialization and enrichment, the network manager validates the knowledge structurally. This ensures the logical consistency of the base which is then checked for inconsistencies and ambiguities specific to the domain of software requirements.From a software engineering point of view, the originality of DASERT is that it provides a semantic checking of an informal specification by interpreting the natural language comments. From a knowledge acquisition point of view, DASERT allows acquisition from texts to build the kernel of a knowledge base which is then used to guide the semantic parsing of texts during the acquisition of the specification itself. Moreover, the representation formalism provides a unified view of acquisition and validation. 相似文献
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[目的/意义]针对基于内容的个性化推荐策略，提出资源特征选择与权值计算优化策略，从而改善个性化推荐的效果。[方法/过程]构建基于用户决策机理的个性化推荐模型，模型以用户决策机理为背景知识进行资源特征的选择、用户兴趣模型的构建与语义表示、用户决策函数构建。为验证模型效果，以4 748位用户的观影数据为例进行实验，实验以向量空间模型为参照模型，P@N为评价指标。[结果/结论]实验结果显示，在N取值为5、10、20、50、100、200的情况下，基于用户决策机理的个性化推荐模型效果都显著优于向量空间模型，从而验证模型的有效性。 相似文献
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数字图像的语义描述与标注是解决图像检索中语义鸿沟问题的关键。由于缺乏面向领域的有效的数字图像描述方法规范,基于图像底层视觉特征的机器标注和基于专家知识的人为标注的标注结果都存在标注信息质量不高和结果不统一的问题。针对这一现实问题,本文基于图像元数据和信息需求理论,针对敦煌壁画数字图像这一特定文化遗产领域,提出了语义描述框架和领域主题词表相结合的数字图像内容语义描述方法,详细阐述了语义层次及其相互关系。同时,从图像语义描述粒度的角度讨论了语义粒度大小对标注成本的影响,以及该语义描述框架的可移植性问题。图4。表5。参考文献25。 相似文献