混合多层分类和朴素贝叶斯模型的垂直搜索引擎分类器设计

研究Web上计算机教育资源的分布特点,融合主题词和文档形式,设计多层分类器来完成主题搜索过程中的正确分类,继而应用朴素贝叶斯模型对主题资源信息进行自动类别划分,完成资源的物理存储。实验中主题分类的平均正确率约78%,主题的平均召回率约61%,而资源解析的平均正确率约81.5%,测试结果能够验证本文设计思想的可行性。     

图书全程策划的实务与技巧

图书运作的全过程中,策划编辑扮演着总设计师的角色;在这个过程的各个阶段,策划编辑扮演的角色各不相同。本文分选题策划、组稿、审稿和加工、书名和辅文设计、装帧设计、推广与营销几个阶段,阐述如何对一本书进行全程策划。     

Web环境下的科技新闻主题挖掘——以国际极地考察领域为例

提出一种基于LDA主题模型的科技新闻主题分析方法,选取2009—2018年中、澳、英、美4国极地科考新闻数据,从主题类型和主题强度角度进行主题演化分析。在中文新闻中,极地测绘等主题的热度上升,极地冰川科考主题的热度下降;在英文新闻中,热门主题为极地冰川科考与极地海洋科考;其余主题热度相对稳定。研究结果表明,该方法可以有效识别科技新闻主题并揭示其演化趋势,可以有效改善网络环境下科技情报分析的自动化程度。     

Topic Driven Adaptive Network for cross-domain sentiment classification

As a hot spot these years, cross-domain sentiment classification aims to learn a reliable classifier using labeled data from a source domain and evaluate the classifier on a target domain. In this vein, most approaches utilized domain adaptation that maps data from different domains into a common feature space. To further improve the model performance, several methods targeted to mine domain-specific information were proposed. However, most of them only utilized a limited part of domain-specific information. In this study, we first develop a method of extracting domain-specific words based on the topic information derived from topic models. Then, we propose a Topic Driven Adaptive Network (TDAN) for cross-domain sentiment classification. The network consists of two sub-networks: a semantics attention network and a domain-specific word attention network, the structures of which are based on transformers. These sub-networks take different forms of input and their outputs are fused as the feature vector. Experiments validate the effectiveness of our TDAN on sentiment classification across domains. Case studies also indicate that topic models have the potential to add value to cross-domain sentiment classification by discovering interpretable and low-dimensional subspaces.     

Schema and constraints-based matching and merging of Topic Maps

In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Our multi-strategic matching approach consists of a linguistic module and a Topic Map constraints-based module. A linguistic module computes similarities between concepts using morphological analysis, string normalization and tokenization and language-dependent heuristics. A Topic Map constraints-based module takes advantage of several Topic Maps-dependent techniques such as a topic property-based matching, a hierarchy-based matching, and an association-based matching. This is a composite matching procedure and need not generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the Topic Maps. Merging between Topic Maps follows the matching operations. We set up the MERGE function to integrate two Topic Maps into a new Topic Map, which satisfies such merge requirements as entity preservation, property preservation, relation preservation, and conflict resolution. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Wikipedia philosophy ontology as input ontologies. Our experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations.     

“借题目写性情”——《儿女英雄传》主题新探

《儿女英雄传》的主题一向以“宣扬封建忠孝节义”著称，本文从作者本身的创作意图、作品人物形象的塑造、作品情节结构的设置等几个方面详加考察，否定了这一传统观点，提出了“借题目写性情”的新主题观，肯定了作品的时代进步性。     

新课标观照下的中考语文试题特点分析

自新课改实施以来,各地中考语文试题,尽管在题型设置、选材风格、制卷样式上存在差异,但在诸多理论和实践问题上存在共性,都能运用新课标、新理论、新思路、新技巧于测试中,以读写为轴心自然展开,更加关注对学生语文素养的考查,体现出贴近生活、题型开放、偏重主观表达的特点。     

与话题相关的介词“对”的隐现

本文主要讨论现代汉语介词“对”的隐现问题。研究表明：“对”的省略必须满足三个条件,即句法上,“对”字结构位于句首作状语;语义上,在“对”介引的成分与动词或动词宾语有隐性语义关系前提下,如果“对”后边的名词性成分中包含指示代词或疑问代词,“对”可以隐藏,如果该名词性成分是降格的受事论元,“对”也可以隐藏;音节上,“时”介引的必须是非单音节词。     

Topic distillation via sub-site retrieval

Topic distillation is one of the main information needs when users search the Web. Previous approaches for topic distillation treat single page as the basic searching unit, which has not fully utilized the structure information of the Web. In this paper, we propose a novel concept for topic distillation, named sub-site retrieval, in which the basic searching unit is sub-site instead of single page. A sub-site is the subset of a website, consisting of a structural collection of pages. The key of sub-site retrieval includes (1) extracting effective features for the representation of a sub-site using both the content and structure information, (2) delivering the sub-site-based retrieval results with a friendly and informative user interface. For the first point, we propose Punished Integration algorithm, which is based on the modeling of the growth of websites. For the second point, we design a user interface to better illustrate the search results of sub-site retrieval. Testing on the topic distillation task of TREC 2003 and 2004, sub-site retrieval leads to significant improvement of retrieval performance over the previous methods based on single pages. Furthermore, time complexity analysis shows that sub-site retrieval can be integrated into the index component of search engines.     

英文报刊杂志标题的修辞色彩

报刊杂志英语充满修辞, 尤以标题最为明显。在任何一种语言中, 修辞手法都是最常见的用于增强表达效果, 使表达更为生动活泼的手段之一。作为一种新的语言分支,报刊杂志英语适合使用各种英语修辞手法, 尤其是用在标题中。它们起着桥梁的作用, 使标题语言更加生动, 具体, 准确, 易懂, 从而使标题内容更加充实丰富。