Word Sense Induction with Closed Frequent Termsets

The article is devoted to the problem of word sense induction. We propose a method for inducing senses from a raw text corpus. The proposed sense induction algorithm (called SenseSearcher, or SnS) is based on closed frequent sets, and as a result, it provides a multilevel sense representation. To a large extent, it is a knowledge‐poor approach, as it does not need any kind of structured knowledge base about senses and there is no deep language knowledge embedded. By discovering a hierarchy of senses, the algorithm enables identifying subsenses (fine‐grained senses). SnS discovers not only frequent (dominating) senses but also infrequent ones (dominated). The method was evaluated in two main areas: lexicography and information retrieval. With the use of the SnS algorithm, we provide a tool able to induce from a textual corpus a structure of senses, with a varying number of granularity levels. In the area of information retrieval, SnS can be used for clustering search result, according to the discovered senses. The experiments have shown that SnS performs better than the methods participating in the SemEval2013 WSI Task 11 competition, and most of the known search result clustering methods.     

联动“五感”产品设计风格

现今的产品设计已经突破了单纯的靠外型或功能吸引消费者的时代,转而进入了一个五感(视觉、听觉、触觉、嗅觉、味觉)联动的年代。优秀的产品往往给人以多重感受的惊喜。文章以人的五感作为切入点,从五感交织性、相互影响性为视角,简述了视觉思维、产品信息在头脑的构建过程以及全身遍布的大脑(感觉的联动性)。进而分析了联动五感的产品设计原则的形成原因、起作用过程、以及应用价值。     

五感体验式教学的探索与应用研究——以环境景观设计课程为例

体验式教学研究是教学理论研究中的一个比较新的课题，文章在总结归纳体验式教学研究的基础上。针对环境景观设计的专业特点发展出“五感体验式教学”，从概念上对其作出阐释，并结合环境景观设计课程教学实践。系统详细地论述了五感体验式教学的主要内容，最后总结了五感体验式教学的理论价值与实践意义。     

五官在人脸识别中的作用权值研究

研究人脸五官局部特征在人脸识别中的作用,按五官所起作用大小将其量化,量化后的值即为作用权值。对五官定位并划分区域,每个区域采用主成分分析进行特征选择。利用改进遗传算法计算每个区域特征向量的数量,将其组合使识别率达到最大。实验结果表明,利用支持向量机进行识别,在识别率最大的前提下,各个区域特征向量所占比例即为作用权值。     

基于路径与深度的同义词词林词语相似度计算

该文提出了一种基于路径与深度的同义词词林词语语义相似度计算方法。该方法通过两个词语义项之间的最短路径以及它们的最近公共父结点在层次树中的深度计算出两个词语义项的相似度。在处理两个词语义项的最短路径与其最近公共父结点的深度时,为提高路径与深度计算的合理性,为分类树中不同层之间的边赋予不同的权值,同时通过两个义项在其最近公共父结点中的分支间距动态调节词语义项间的最短路径,从而平衡两个词语的相似度。该方法修正了目前相关算法只能得出几个固定的相似度值,所有最近公共父结点处于同一层次的义项对之间的相似度都相同的不合理现象,使词语语义相似度的计算结果更为合理。实验表明,该方法对MC30词对的相似度计算值与人工判定值相比,取得了0.856的皮尔逊相关系数,该结果高于目前大多数词语相似度算法与MC30的相关度。
     

"I Don’t Believe in Word Senses"

Word sense disambiguation assumes word senses. Withinthe lexicography and linguistics literature, they areknown to bevery slippery entities. The first part of the paperlooks at problemswith existing accounts of ‘word sense’ and describesthe various kinds of ways in which a word's meaning candeviate from its coremeaning. An analysis is presented in which wordsenses areabstractions from clusters of corpus citations, inaccordance withcurrent lexicographic practice. The corpus citations,not the wordsenses, are the basic objects in the ontology. Thecorpus citationswill be clustered into senses according to thepurposes of whoever or whatever does the clustering. In theabsence of suchpurposes, word senses do not exist. Word sense disambiguation also needs a set of wordsenses todisambiguate between. In most recent work, the sethas been takenfrom a general-purpose lexical resource, with theassumption that thelexical resource describes the word senses ofEnglish/French/...,between which NLP applications will need todisambiguate. Theimplication of the first part of the paper is, bycontrast, that wordsenses exist only relative to a task. Thefinal part of the paper pursues this, exploring, bymeans of asurvey, whether and how word sense ambiguity is infact a problem forcurrent NLP applications.     

Accommodating mixed sensory/modal preferences in collaborative writing systems

Writers use the abstractions of words to create meaning. But the activity of writing spans multiple concrete senses and modes. Technology-enhanced collaborative writing systems need to be sensitive to the preferred senses and modes of information in which writing teams want to work. Some preferences seem rooted in the senses (seeing vs. motor coordination); others seem based in the preferred modality of inputting or outputting information (speaking vs. writing; listening vs. reading). Still others seem based in the role of the writer on the team (author or commenter). We offer a framework for understanding some of these preferences and a prototype editor (the Prep Editor) we have been using to study them empirically.     

用于中文分词的组合型歧义消解算法

自动分词技术的瓶颈是切分歧义,切分歧义可分为交集型切分歧义和组合型切分歧义。以组合型歧义字段所在句子为研究对象,考察歧义字段不同切分方式所得结果与其前后搭配所得词在全文中的支持度,构造从合或从分切分支持度度量因子,依据该因子消除组合型歧义。通过样例说明和实验验证该方法可行并优于现有技术。     

一种基于背景知识的本体注释方法

本体采用基于语法词汇的表述方式,使本体自身表示可能存在模糊性、错误理解等问题,部分本体的概念可以通过自身的上下文信息推测出其含义,但是有些本体根据已有信息不能清晰表达其概念的确切含义.针对这个问题,提出基于背景知识的本体注释方法,对本体本身进行注释和澄清.包括基于WordNet和Web搜索引擎的注释方法,利用WordNet查找本体概念的正确词义,利用Web搜索引擎搜索本体概念的snippets,分别将词义和snippets作为其属性注释到本体中.实验表明本体注释率达到99.12％,表明本文方法的是可行的,本体注释正确率达到80.76％,比同类方法更高.     

PQAC-WN: constructing a wordnet for Pre-Qin ancient Chinese

The Princeton WordNet^® (PWN) is a widely used lexical knowledge database for semantic information processing. There are now many wordnets under creation for languages worldwide. In this paper, we endeavor to construct a wordnet for Pre-Qin ancient Chinese (PQAC), called PQAC WordNet (PQAC-WN), to process the semantic information of PQAC. In previous work, most recently constructed wordnets have been established either manually by experts or automatically using resources from which translation pairs between English and the target language can be extracted. The former method, however, is time-consuming, and the latter method, owing to a lack of language resources, cannot be performed on PQAC. As a result, a method based on word definitions in a monolingual dictionary is proposed. Specifically, for each sense, kernel words are first extracted from its definition, and the senses of each kernel word are then determined by graph-based Word Sense Disambiguation. Finally, one optimal sense is chosen from the kernel word senses to guide the mapping between the word sense and PWN synset. In this research, we obtain 66 % PQAC senses that can be shared with English and another 14 % language-specific senses that were added to PQAC-WN as new synsets. Overall, the automatic mapping achieves a precision of over 85 %.     

A contribution to a multimodal approach to knowledge modeling

At present a steep increase in efforts by human beings in search of information take place. Pattern Recognition extracts information from the real world. It is a tool for modelling and real-world learning. Thus it requires precise knowledge of the objectives to be achieved with the information it produces. Human senses are part of their interface with the environment. Our senses are signal encoders according some representation that is understood by the central nervous system. Multimodality in signal capturing makes the spectrum of activities of intelligent agents wider. This paper aims to stimulate research for providing multimodal information, say, information that can be captured by different senses. This technique can improve decision-making; promote the inclusion of sense disabled individuals, giving higher amplitude for usefulness of Pattern Recognition. It considers multimodal display of knowledge to practical feasibility of knowledge presentation adapted to human sensing and perception towards decision improvement and inclusion of perception-impaired people.     

英语语音合成中基于WordNet的多音词消歧算法

英语中的多音词分成两类,一是因词性不同而读音不同,一是因词义不同而读音不同。前者只需经词性标注,根据其词性标记就可判别其正确的读音。而后者则复杂得多,论文采用了一种基于WordNet语义信息的多音词消歧算法,该算法将多音词的语义信息与上下文中词的语义信息进行匹配,根据匹配结果来判别多音词的读音。     

基于HowNet的信息量计算语义相似度算法

语义相似度计算的应用范围广泛,从心理学、语言学、认知科学到人工智能都有其应用.提出了仅依赖于知网(HowNet)的信息量计算来估计两个词汇间的语义相似度.经实验证明,相比于传统的基于词网(WordNet)和大型语料库的计算信息量来估计语义相似度的算法,本文的算法更容易计算,并更接近于人工的语义相似度判断.     

Dictionary word sense distinctions: An enquiry into their nature

The word senses in a published dictionary are a valuable resource for natural language processing and textual criticism alike. In order that they can be further exploited, their nature must be better understood. Lexicographers have always had to decide where to say a word has one sense, where two. The two studies described here look into their grounds for making distinctions. The first develops a classification scheme to describe the commonly occurring distinction types. The second examines the task of matching the usages of a word from a corpus with the senses a dictionary provides. Finally, a view of the ontological status of dictionary word senses is presented.Adam Kilgarriff has recently completed his doctoral thesis, entitled Polysemy, available as CSRP 261, from the School of Cognitive and Computing Science, University of Sussex. He is now working on the preparation of database versions of dictionaries for language research for Longman Dictionaries.     

"回收站"的使用技巧

介绍回收站几种使用的常识和技巧.     

Choosing Rhetorical Structures To Plan Instructional Texts

This paper discusses a fundamental problem in natural language generation: how to organize the content of a text in a coherent and natural way. In this research, we set out to determine the semantic content and the rhetorical structure of texts and to develop heuristics to perform this process automatically within a text generation framework. The study was performed on a specific language and textual genre: French instructional texts. From a corpus analysis of these texts, we determined nine senses typically communicated in instructional texts and seven rhetorical relations used to present these senses. From this analysis, we then developed a set of presentation heuristics that determine how the senses to be communicated should be organized rhetorically in order to create a coherent and natural text. The heuristics are based on five types of constraints: conceptual, semantic, rhetorical, pragmatic, and intentional constraints. To verify the heuristics, we developed the spin natural language generation system, which performs all steps of text generation but focuses on the determination of the content and the rhetorical structure of the text.     

嗅觉符号在平面广告中的应用初探

人类有五种感觉:视觉、听觉、触觉、嗅觉和味觉,其中嗅觉是最神秘的一种感官。人们在每天的工作、生活中接触最多的是各种图像、文字和声音,它们带给人们的是视觉和听觉上的感受,我们生活中80%的信息是通过视觉和听觉感官接收的。文章结合符号学的知识,从嗅觉感官入手,初步探讨了嗅觉符号及其在设计中的应用。气味作为一种符号,成为平面广告设计的可能。     

基于语义密度的名词消歧算法

提出了一种以概念相关性为主要依据的名词消歧算法。与现有算法不同的是,该算法在WordNet上对两个语义之间的语义距离进行了拓展,定义了一组语义之间的语义密度,从而量化了一组语义之间的相关性。将相关性转化为语义密度后,再进行消歧。还提出了一种在WordNet上的类似LSH的语义哈希,从而大大降低了语义密度的计算复杂度以及整个消歧算法的计算复杂度。在SemCor上对该算法进行了测试和评估。     

Evaluation of fitting of plastic parts

Abstract

As an example of measurement by touch, fitting of plastic parts was studied. Where such requirement is dependent on judgement made by human senses, a number of characteristics must be measured in order to obtain the mechanical characteristics matching those of touch. The degree of fitting judged by touch is quantified by multidimensional scaling, using capsule-shaped plastic parts. Also, the dimensions, shapes and the degree of mechanical fitting are measured and the relationships of these to the quantified senses determined by factor analysis, multivariate data analysis being effective for this purpose.