大学生权利意识的实证分析与培养方式研究     

陆在春  杨扬 《芜湖师专学报》2013,(2):20-23

大学生的权利意识包括权利主体意识、权利实现意识和权利救济意识。调查表明,大学生的权利主体意识逐渐增强,权利实现意识具体、明晰,而义务承担意识虚无,权利救济意识薄弱。大学生权利意识需要通过依法治教,加强法治教育课程建设等途径培养。  相似文献   

辐射板强化喷管换热与红外抑制效果试验研究     

张勃  吉洪湖  黄伟  蔡旭  张宗斌  罗明东 《唐山学院学报》2013,(4):445-450

试验研究了在发动机喷管中加装金属辐射板前后,喷管壁面温度、热喷流温度与喷管红外辐射特征的变化。结果表明,加装金属辐射板后,热喷流与喷管壁面之间的热量传递显著增强,热喷流中心温度降低,壁面温度明显升高,在90°方向上,热喷流3～5μm波段的红外辐射强度降低了38.5%。文中从热喷流、喷管壁面以及金属辐射板等相关部件的温度变化情况对红外辐射强度的变化原因进行了解释。   相似文献   

Using semantic similarity to reduce wrong labels in distant supervision for relation extraction     

Chengsen Ru  Jintao Tang  Shasha Li  Songxian Xie  Ting Wang 《Information processing & management》2018,54(4):593-608

Distant supervision (DS) has the advantage of automatically generating large amounts of labelled training data and has been widely used for relation extraction. However, there are usually many wrong labels in the automatically labelled data in distant supervision (Riedel, Yao, & McCallum, 2010). This paper presents a novel method to reduce the wrong labels. The proposed method uses the semantic Jaccard with word embedding to measure the semantic similarity between the relation phrase in the knowledge base and the dependency phrases between two entities in a sentence to filter the wrong labels. In the process of reducing wrong labels, the semantic Jaccard algorithm selects a core dependency phrase to represent the candidate relation in a sentence, which can capture features for relation classification and avoid the negative impact from irrelevant term sequences that previous neural network models of relation extraction often suffer. In the process of relation classification, the core dependency phrases are also used as the input of a convolutional neural network (CNN) for relation classification. The experimental results show that compared with the methods using original DS data, the methods using filtered DS data performed much better in relation extraction. It indicates that the semantic similarity based method is effective in reducing wrong labels. The relation extraction performance of the CNN model using the core dependency phrases as input is the best of all, which indicates that using the core dependency phrases as input of CNN is enough to capture the features for relation classification and could avoid negative impact from irrelevant terms.  相似文献   

Neural embedding-based indices for semantic search     

Fatemeh Lashkari  Ebrahim Bagheri  Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755

Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献   

A knowledge-based semantic framework for query expansion     

Jamal Abdul Nasir  Iraklis Varlamis  Samreen Ishfaq 《Information processing & management》2019,56(5):1605-1617

Searching for relevant material that satisfies the information need of a user, within a large document collection is a critical activity for web search engines. Query Expansion techniques are widely used by search engines for the disambiguation of user’s information need and for improving the information retrieval (IR) performance. Knowledge-based, corpus-based and relevance feedback, are the main QE techniques, that employ different approaches for expanding the user query with synonyms of the search terms (word synonymy) in order to bring more relevant documents and for filtering documents that contain search terms but with a different meaning (also known as word polysemy problem) than the user intended. This work, surveys existing query expansion techniques, highlights their strengths and limitations and introduces a new method that combines the power of knowledge-based or corpus-based techniques with that of relevance feedback. Experimental evaluation on three information retrieval benchmark datasets shows that the application of knowledge or corpus-based query expansion techniques on the results of the relevance feedback step improves the information retrieval performance, with knowledge-based techniques providing significantly better results than their simple relevance feedback alternatives in all sets.  相似文献   

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis     

Kai Hu  Qing Luo  Kunlun Qi  Siluo Yang  Jin Mao  Xiaokang Fu  Jie Zheng  Huayi Wu  Ya Guo  Qibing Zhu 《Information processing & management》2019,56(4):1185-1203

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.  相似文献   

大学英语词汇教学策略     

刘卫华 《漯河职业技术学院学报》2007,6(2):61-62

词汇教学在大学英语教学中至关重要.目前词汇教学存在种种误区,成为制约学生学好英语的障碍.本文探讨了语境策略、精加工策略、语义场策略、词块记忆策略和元认知策略,以改进大学英语词汇教学现状.  相似文献   

Social support and digital inequality: Does Internet use magnify or mitigate traditional inequities in support availability?     

Stephen A. Rains  Eric Tsetsi 《Communication monographs》2017,84(1):54-74

This study tested competing predictions about the implications of Internet use for traditional inequities in social support availability. Using survey data collected as part of the Pew Internet and American Life Project, inequities in social support availability stemming from demographic and network-related factors were examined among non-users, Internet users, and Internet users who also participated in a social network site (SNS). The results offered evidence consistent with the social compensation perspective. Traditional inequities in support availability related to age, race, and total network size persisted among respondents who did not use the Internet, but were less evident or absent among Internet users and/or Internet users who participated in an SNS. Using the Internet to connect with others appeared to be an important mechanism through which inequality in support availability was mitigated.  相似文献   

第三方物流企业客户忠诚度评价及提升     

陶雪萍 《五邑大学学报(社会科学版)》2008,10(2):61-64

随着第三方物流行业竞争的日益激烈,评价及提升客户忠诚度已成为企业发展的重要问题。对客户忠诚度可从客户满意、转换成本、关系信任、重复购买、客户推荐、交叉购买、价格敏感等方面进行评价并建立相应的测量指标体系,又可从提高客户满意度、对企业的信任度以及转换成本等方面提升客户的忠诚度。  相似文献   

新兴“X活族”词语及其语用修辞价值     

刘红妮 《毕节师范高等专科学校学报》2008,(6):17-20

“X活族”新词是指“快活族”、“慢活族”、“乐活族”这样新出现的带“活族”的词语。“X活族”新词的句法和语义构成比较复杂;语用上具有继承性与创新性、二次创新和非常规性、音译兼意译,洋为中用的特点;修辞上巧用对比、转喻和概念整合手段,具有形象创新、词约义丰、直指本质以及陌生化的功能。“X活族”新词的涌现,是语言和社会共同作用的结果。  相似文献