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上下文感知是实现普适计算环境中新型人机交互的基础。针对上下文不一致性的消除问题,提出了全丢弃算法、最新上下文丢弃算法、基于确定性上下文丢弃算法和基于相关性的上下文丢弃算法,并对算法的性能进行了比较和分析。实验测试表明,这些算法能够有效消除上下文不一致性。 相似文献
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词语相似度计算方法在信息检索、词义消歧、机器翻译等自然语言处理领域有着广泛的应用。现有的词语相似度算法主要分为基于统计和基于语义资源两类方法,前者是从大规模的语料中统计与词语共现的上下文信息以计算其相似度,而后者利用人工构建的语义词典或语义网络计算相似度。本文比较分析了两类词语相似度算法,重点介绍了基于Web语料库和基于维基百科的算法,并总结了各自的特点和不足之处。最后提出,在信息技术的影响下,基于维基百科和基于混合技术的词语相似度算法以及关联数据驱动的相似性计算具有潜在的发展趋势。 相似文献
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在文本中,常常出现一词多义的现象,本文提出一种基于语义关系图的词义消歧算法,算法首先利用Word Net的语义关系构建语义关系图;其次,通过多义词在语义关系图的上下文选择最佳语义关系。测试用Senseval-3中的全文内容作为实验测试集,结果表明,词义消歧算法的测试结果很理想。 相似文献
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上下文对用户搜索行为的影响 总被引：1，自引：0，他引：1
用户的搜索是在特定搜索上下文中进行的,虽然个性化搜索、社会化搜索可以利用一部分上下文信息,但有时搜索效果因搜索引擎未有效利用其他上下文信息而让人无法接受.论文采用发放问卷调查的方式,探索上下文信息对用户搜索行为的影响.首先针对用户上下文、查询上下文、页面上下文分别设计一定数量的调查题目;其次在新浪等五个网站发放问卷,收集为期一个月的互联网用户反馈结果,得到数据集;最后,分析三类Web上下文信息对用户搜索行为的影响.结果显示:查询上下文影响权重最大、用户上下文次之、页面上下文的影响最小,这一结果可为有效利用上下文信息提供一定的借鉴作用. 相似文献
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语文新课程标准总体目标与内容规定培育学生热爱祖国语言文字的情感,增加学生学习语文的自信心,养成良好的语文学习习惯,初步掌握学习语文的基本方法.分段目标指出1、2年级结合上下文和生活实际了解课文中词语的意思.在阅读中积累词语,在写活中乐于运用阅读和生活中学到的词语.3、4年级积累课文中的优美词语,在习作中尝试运用自己积累的词语,表达自己的思想感情.5、6年级推想课文中有关词语的意思,辨别词语的感情色彩,体会其表达效果.那么词语在我们现实生活中如此重要,怎样才能把语文词语的学习方法教给学生呢? 相似文献
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《Information processing & management》2020,57(6):102273
Vital to the task of Sentiment Analysis (SA), or automatically mining sentiment expression from text, is a sentiment lexicon. This fundamental lexical resource comprises the smallest sentiment-carrying units of text, words, annotated for their sentiment properties, and aids in SA tasks on larger pieces of text. Unfortunately, digital dictionaries do not readily include information on the sentiment properties of their entries, and manually compiling sentiment lexicons is tedious in terms of annotator time and effort. This has resulted in the emergence of a large number of research works concentrated on automated sentiment lexicon generation. The dictionary-based approach involves leveraging digital dictionaries, while the corpus-based approach involves exploiting co-occurrence statistics embedded in text corpora. Although the former approach has been exhaustively investigated, the majority of works focus on terms. The few state-of-the-art models concentrated on the finer-grained term sense level remain to exhibit several prominent limitations, e.g., the proposed semantic relations algorithm retrieves only senses that are at a close proximity to the seed senses in the semantic network, thus prohibiting the retrieval of remote sentiment-carrying senses beyond the reach of the ‘radius’ defined by number of iterations of semantic relations expansion. The proposed model aims to overcome the issues inherent in dictionary-based sense-level sentiment lexicon generation models using: (1) null seed sets, and a morphological approach inspired by the Marking Theory in Linguistics to populate them automatically; (2) a dual-step context-aware gloss expansion algorithm that ‘mines’ human defined gloss information from a digital dictionary, ensuring senses overlooked by the semantic relations expansion algorithm are identified; and (3) a fully-unsupervised sentiment categorization algorithm on the basis of the Network Theory. The results demonstrate that context-aware in-gloss matching successfully retrieves senses beyond the reach of the semantic relations expansion algorithm used by prominent, well-known models. Evaluation of the proposed model to accurately assign senses with polarity demonstrates that it is on par with state-of-the-art models against the same gold standard benchmarks. The model has theoretical implications in future work to effectively exploit the readily-available human-defined gloss information in a digital dictionary, in the task of assigning polarity to term senses. Extrinsic evaluation in a real-world sentiment classification task on multiple publically-available varying-domain datasets demonstrates its practical implication and application in sentiment analysis, as well as in other related fields such as information science, opinion retrieval and computational linguistics. 相似文献
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在分析基于搜索引擎的术语相似度算法基础上,设计并实现了基于领域限定网络检索的术语相似度算法,通过将语义上下文和领域上下文引入检索式构造过程,有效提升了特定领域术语相似度计算效果。 相似文献
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基于本体的文本信息检索研究 总被引：5，自引：0，他引：5
本文对如何构建基于本体的文本信息检索系统进行了探讨．并认为，利用反映概念之间关系的领域本体指导主题标引，利用反映实体之间关系的领域本体指导实体关系标引，并以本体的形式表示文档替代物和查询表达式，可以进一步提高文本信息检索系统的性能。 相似文献
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知识检索过程必须借助于语言工具来实现,这一过程在用户同系统知识库的交互中,表现为知识→语言→知识→……的互相转换过程。在知识检索中普遍存在语境支持等语用现象,这些现象尤其集中存在于人机交互的检索界面,而其中的锚文本等及其分布构成了检索交流中重要的语境支持信息。知识检索系统界面的语用设计直接决定了系统检索的成效。系统界面及锚文本的语用设计的基本要求包括语境充分和整体优化等。 相似文献
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用户当前正在浏览的网页内容有助于说明用户的即时信息需求.在现有相关研究的基础上提出了一种基于上下文的Web即时信息检索方法,该方法允许用户从正在浏览的网页中选择一段文本作为原始检索条件,由检索系统从其上下文中提取一级扩展词和二级扩展词来形成新的检索条件进行检索,并将检索结果按相似度从大到小的顺序呈现给用户. 相似文献
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Mouna Torjmen-Khemakhem Karen Pinel-Sauvagnat Mohand Boughanem 《Information processing & management》2013
Multimedia objects can be retrieved using their context that can be for instance the text surrounding them in documents. This text may be either near or far from the searched objects. Our goal in this paper is to study the impact, in term of effectiveness, of text position relatively to searched objects. The multimedia objects we consider are described in structured documents such as XML ones. The document structure is therefore exploited to provide this text position in documents. Although structural information has been shown to be an effective source of evidence in textual information retrieval, only a few works investigated its interest in multimedia retrieval. More precisely, the task we are interested in this paper is to retrieve multimedia fragments (i.e. XML elements having at least one multimedia object). Our general approach is built on two steps: we first retrieve XML elements containing multimedia objects, and we then explore the surrounding information to retrieve relevant multimedia fragments. In both cases, we study the impact of the surrounding information using the documents structure. 相似文献
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从语用视角对知识检索进行考察具有重要意义。在知识检索过程中,用户的检索行为表现出的各种特征,都表明语境支持等语用现象普遍存在于检索过程中。这些现象尤其集中存在于人—机交互的检索界面,而检索界面中的文本及其分布结构构成了检索交流中最基本的语境信息载体。在语用视角下,知识检索的界面设计必须遵循的基本原则包括语境信息充分原则、最小努力够用原则,以及及时更新和持续发展原则等。 相似文献
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Automatic text classification is the task of organizing documents into pre-determined classes, generally using machine learning algorithms. Generally speaking, it is one of the most important methods to organize and make use of the gigantic amounts of information that exist in unstructured textual format. Text classification is a widely studied research area of language processing and text mining. In traditional text classification, a document is represented as a bag of words where the words in other words terms are cut from their finer context i.e. their location in a sentence or in a document. Only the broader context of document is used with some type of term frequency information in the vector space. Consequently, semantics of words that can be inferred from the finer context of its location in a sentence and its relations with neighboring words are usually ignored. However, meaning of words, semantic connections between words, documents and even classes are obviously important since methods that capture semantics generally reach better classification performances. Several surveys have been published to analyze diverse approaches for the traditional text classification methods. Most of these surveys cover application of different semantic term relatedness methods in text classification up to a certain degree. However, they do not specifically target semantic text classification algorithms and their advantages over the traditional text classification. In order to fill this gap, we undertake a comprehensive discussion of semantic text classification vs. traditional text classification. This survey explores the past and recent advancements in semantic text classification and attempts to organize existing approaches under five fundamental categories; domain knowledge-based approaches, corpus-based approaches, deep learning based approaches, word/character sequence enhanced approaches and linguistic enriched approaches. Furthermore, this survey highlights the advantages of semantic text classification algorithms over the traditional text classification algorithms. 相似文献
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单汉字索引是中文全文检索索引技术中一个主要方法，此方法在索引的空问和检索的效率方面都存在不足。本文引入单元词索引，并分析试验数据，表明引入单元词索引后，索引的空间效率和检索的时间效率均有提高。 相似文献