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   

网络招聘文本技能信息自动抽取研究   总被引：1，自引：1，他引：0  

俞琰  陈磊  姜金德  赵乃瑄 《图书情报工作》2019,63(13):105-113

[目的/意义]针对目前网络招聘文本手工抽取技能信息无法满足大数据量分析要求的问题，提出一种针对大量网络招聘文本的技能信息自动抽取方法。[方法/过程]根据网络招聘文本的特点，利用依存句法分析选取候选技能，然后提出领域相关性指标衡量候选技能，将其融入传统的术语抽取方法之中，形成一种网络招聘文本技能信息自动抽取方法。[结果/结论]实验表明，本文提出的方法能够从网络招聘文本中自动、快速、准确地抽取技能信息。  相似文献   

Self-training on refined clause patterns for relation extraction     

Duc-Thuan Vo  Ebrahim Bagheri 《Information processing & management》2018,54(4):686-706

Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques.  相似文献   

Local word vectors guiding keyphrase extraction     

Eirini Papagiannopoulou  Grigorios Tsoumakas 《Information processing & management》2018,54(6):888-902

Automated keyphrase extraction is a fundamental textual information processing task concerned with the selection of representative phrases from a document that summarize its content. This work presents a novel unsupervised method for keyphrase extraction, whose main innovation is the use of local word embeddings (in particular GloVe vectors), i.e., embeddings trained from the single document under consideration. We argue that such local representation of words and keyphrases are able to accurately capture their semantics in the context of the document they are part of, and therefore can help in improving keyphrase extraction quality. Empirical results offer evidence that indeed local representations lead to better keyphrase extraction results compared to both embeddings trained on very large third corpora or larger corpora consisting of several documents of the same scientific field and to other state-of-the-art unsupervised keyphrase extraction methods.  相似文献   

基于无人机激光点云的树障检测与砍伐树木数量估算     

张苏  齐立忠  韩文军  朱笑笑  习晓环  王成  王濮  聂胜 《中国科学院大学学报》2020,37(6):760-766

电力走廊的树木生长会对输电线路的安全运营造成巨大影响，精确检测出影响线路安全的树木并将其砍伐至关重要。因此，提出一种基于无人机激光点云的树障检测与砍伐树木数量估算方法。首先，对激光点云进行快速自动化处理，先后精确提取地面点、电力线点与植被点；其次，基于电力线点进行分段，并分析电力线与植被点的安全距离，进而确定树障区域的位置和范围；最后，对树障区域植被点云进行单木分割，并统计单木数量，最终实现砍伐树木数量的精准估算。研究结果表明，无人机激光点云可以实现输电通道树障的有效检测与砍伐树木数量的精确估算，总体树木砍伐数量估算精度可达92.3%，可为输电线路安全运营提供遥感技术支撑，也可为电网运维单位制订树木砍伐计划提供可靠依据。  相似文献   

Ancient Mural Classification Method Based on Improved AlexNet Network     

Jianfang Cao  Hongyan Cui  Qi Zhang  Zibang Zhang 《文物保护研究》2020,65(7):411-423

ABSTRACT

As an important part of art and culture, ancient murals depict a variety of different artistic images, and these individual images have important research value. For research purposes, it is often important to first determine the type of objects represented in a painting. However, the mural painting environment makes datasets difficult to collect, and long-term exposure leads to underlying features that are not distinct, which makes this task challenging. This study proposes a convolutional neural network model based on the classic AlexNet network model and combines it with feature fusion to automatically classify ancient mural images. Due to the lack of large-scale mural datasets, the model first expands the dataset by applying image enhancement algorithms such as scaling, brightness conversion, noise addition, and flipping; then, it extracts the underlying features (such as fresco edges) shared by the first stage of a dual channel structure. Subsequently, a second-stage deep abstraction is conducted on the features extracted by the first stage using a two-channel network, each of which has a different structure. The obtained characteristics from both channels are merged, and a loss function is constructed to obtain the classification result. This approach improves the model's robustness and feature expression ability. The model achieves an accuracy of 84.24%, a recall rate of 84.15%, and an F1-measure of 84.13% when applied to a constructed mural image dataset. Compared with the AlexNet model and other improved convolutional neural network models, the proposed model improves each evaluation index by approximately 5%, verifying the rationality and effectiveness of the model for automatic mural image classification. The mural classification model proposed in this paper comprehensively considers the influences of network width and depth and can extract rich details from mural images from multiple local channels. An effective classification method could help researchers manage and protect mural images in an orderly fashion and quickly and effectively search for target images in a digital mural library based on a specified image category, aiding mural condition monitoring and restoration efforts as well as archaeological and art historical research.  相似文献   

Combined effects of exposure to hypoxia and cool on walking economy and muscle oxygenation profiles at tibialis anterior     

Masahiro Horiuchi  Yoko Handa-Kirihara  Daijiro Abe  Yoshiyuki Fukuoka 《Journal of sports sciences》2019,37(14):1638-1647

We investigated combined effects of ambient temperature (23°C or 13°C) and fraction of inspired oxygen (21%O₂ or 13%O₂) on energy cost of walking (C_w: J·kg^?1·km^?1) and economical speed (ES). Eighteen healthy young adults (11 males, seven females) walked at seven speeds from 0.67 to 1.67 m s^?1 (four min per stage). Environmental conditions were set; thermoneutral (N: 23°C) with normoxia (N: 21%O₂) = NN; 23°C (N) with hypoxia (H: 13%O₂) = NH; cool (C: 13°C) with 21%O₂ (N) = CN, and 13°C (C) with 13%O₂ (H) = CH. Muscle deoxygenation (HHb) and tissue O₂ saturation (StO₂) were measured at tibialis anterior. We found a significantly slower ES in NH (1.289 ± 0.091 m s^?1) and CH (1.275 ± 0.099 m s^?1) than in NN (1.334 ± 0.112 m s^?1) and CN (1.332 ± 0.104 m s^?1). Changes in HHb and StO₂ were related to the ES. These results suggested that the combined effects (exposure to hypoxia and cool) is nearly equal to exposure to hypoxia and cool individually. Specifically, acute moderate hypoxia slowed the ES by approx. 4%, but acute cool environment did not affect the ES. Further, HHb and StO₂ may partly account for an individual ES.  相似文献   

基于Sentinel-1/2的水体提取方法对比研究——以斯里兰卡小型水体为例     

周晗  叶虎平  魏显虎  张宗科  王法溧  齐永菊  马建如 《中国科学院大学学报》2019,36(6):794-802

地表水面精确提取是研究地表水质和水量变化的重要基础。斯里兰卡是"21世纪海上丝绸之路"的重要参与国，年降雨量丰富，但时空分布不均，斯里兰卡人民长期用水困难，研究斯里兰卡地表水体有助于斯里兰卡民生问题的解决。斯里兰卡国内散布着大量的小型水库和坑塘，这些小面积水体易受周边环境因素影响而提取困难。基于2017年7月斯里兰卡中东部地区的哨兵（Sentinel）1/2号卫星影像，对比分析单波段法、水体指数法和监督分类等水体提取方法的精度和存在的问题。结果表明，归一化水体指数法NDWI的准确率最高，分类精度达94%。  相似文献   

Location extraction from tweets     

Thi Bich Ngoc Hoang  Josiane Mothe 《Information processing & management》2018,54(2):129-144

Five hundred million tweets are posted daily, making Twitter a major social media platform from which topical information on events can be extracted. These events are represented by three main dimensions: time, location and entity-related information. The focus of this paper is location, which is an essential dimension for geo-spatial applications, either when helping rescue operations during a disaster or when used for contextual recommendations. While the first type of application needs high recall, the second is more precision-oriented. This paper studies the recall/precision trade-off, combining different methods to extract locations. In the context of short posts, applying tools that have been developed for natural language is not sufficient given the nature of tweets which are generally too short to be linguistically correct. Also bearing in mind the high number of posts that need to be handled, we hypothesize that predicting whether a post contains a location or not could make the location extractors more focused and thus more effective. We introduce a model to predict whether a tweet contains a location or not and show that location prediction is a useful pre-processing step for location extraction. We define a number of new tweet features and we conduct an intensive evaluation. Our findings are that (1) combining existing location extraction tools is effective for precision-oriented or recall-oriented results, (2) enriching tweet representation is effective for predicting whether a tweet contains a location or not, (3) words appearing in a geography gazetteer and the occurrence of a preposition just before a proper noun are the two most important features for predicting the occurrence of a location in tweets, and (4) the accuracy of location extraction improves when it is possible to predict that there is a location in a tweet.  相似文献   

基于语料库的动态词群建构     

冯文贺 《河南科技学院学报》2014,(9):47-50

提出一个以大规模语料库为资源提取材料,以词汇集为语义成分表达方式的动态词群建构方法,其维度特征值的提取不但具有客观性,而且操作简易。维度特征值用词汇集的方式表示特征取值范围,可以避免传统的义素概括性过强、词汇个性表现不足的缺陷。这种方法有利于面向应用的大规模动态词群的建构。  相似文献