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Improved Internet Resource Recommendation Method using FOAF and SNA 基于FOAF和SNA的改进互联网资源推荐方法
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.165
Qing Wang, Jongsoo Sohn, In-Jeong Chung
In recent years, due to rapidly increasing user-created internet contents coupled with the development of community-based websites, the internet resource recommendation systems are attracting attentions of the users. However, most of the systems have failed in properly reflecting users` characteristics and thus they have difficulty in recommending appropriate resources to users. In this paper, we propose an internet resource recommendation method using FOAF and SNA which fully reflects the characteristics of users. In our method, 1) we extract the data about user characteristics and tags using FOAF; 2) we generate graphs representing users, user characteristics and tags after inserting data into 3 matrixes and integrating them; 3) we recommend the appropriate internet resources after selecting common characteristics of the recommended items and Hot tags by analyzing social network. For verification of our proposed method, we implemented our method to establish and analyze an experimental social group. We verified through our experiments that the more users added in the social network, the higher quality of recommendation result we got than the item-based recommendation method. By using the suggested idea in this paper, we can make a more appropriate recommendation of resources to users while effectively retrieving explosively increasing internet resources.
近年来,由于用户创建的互联网内容迅速增加,加上社区网站的发展,互联网资源推荐系统受到了用户的关注。但是,大多数系统未能适当反映用户的特点,因此难以向用户推荐适当的资源。本文提出了一种充分反映用户特征的基于FOAF和SNA的互联网资源推荐方法。在我们的方法中,1)我们使用FOAF提取关于用户特征和标签的数据;2)将数据插入到3个矩阵中进行积分,生成表示用户、用户特征和标签的图形;3)通过对社交网络的分析,选择被推荐项目的共同特征和热点标签,进行合适的网络资源推荐。为了验证我们提出的方法,我们实施了我们的方法来建立和分析一个实验性的社会群体。我们通过实验验证,在社交网络中加入的用户越多,我们得到的推荐结果质量就越高。利用本文提出的思想,我们可以在有效检索爆炸式增长的互联网资源的同时,为用户提供更合适的资源推荐。
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引用次数: 0
Morpheme Recovery Based on Naïve Bayes Model 基于Naïve贝叶斯模型的语素恢复
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.195
Jae-Hoon Kim, Kil-Ho Jeon
In Korean, spelling change in various forms must be recovered into base forms in morphological analysis as well as part-of-speech (POS) tagging is difficult without morphological analysis because Korean is agglutinative. This is one of notorious problems in Korean morphological analysis and has been solved by morpheme recovery rules, which generate morphological ambiguity resolved by POS tagging. In this paper, we propose a morpheme recovery scheme based on machine learning methods like Nave Bayes models. Input features of the models are the surrounding context of the syllable which the spelling change is occurred and categories of the models are the recovered syllables. The POS tagging system with the proposed model has demonstrated the -score of 97.5% for the ETRI tree-tagged corpus. Thus it can be decided that the proposed model is very useful to handle morpheme recovery in Korean.
在韩国语中,各种形式的拼写变化必须在词形分析中恢复为基本形式,而且由于韩国语具有黏性,如果不进行词性分析,就很难进行词性标注。这是韩国语词法分析中最常见的问题之一,词素恢复规则解决了这一问题,词素恢复规则产生词法歧义,词法标注解决了词法歧义。在本文中,我们提出了一种基于机器学习方法(如Nave Bayes模型)的语素恢复方案。模型的输入特征是发生拼写变化的音节的周围上下文,模型的类别是恢复的音节。使用该模型的词性标注系统对ETRI树标注语料的-得分为97.5%。由此可见,该模型对朝鲜语语素恢复是非常有用的。
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引用次数: 0
Multidimensional Optimization Model of Music Recommender Systems 音乐推荐系统的多维优化模型
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.155
Kyong-Su Park, Nam-Me Moon
This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function R. To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function R for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function R. Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted and the correlation of all variables against the values of the rating function R.
本研究旨在识别音乐推荐系统中的多维变量和子变量,并研究它们在评级函数r最大化时的相对权重。为了完成这项任务,我们在回顾前人关于推荐系统的研究成果的基础上,推导出研究模型的优化公式和变量,并利用这些优化公式和变量建立研究模型进行实证检验。利用研究模型和从韩国某在线音乐提供商获取的真实客户的实际日志数据,进行多元回归分析,得出多维模型中变量的最优相关性。结果表明,物品与评级函数R的相关值最高,其次是社会关系、用户和上下文。在子变量中,来自Social Relations的流行音乐、流派、最新音乐和来自Items的最喜欢的艺术家与评级函数r的相关性很高。同时,衍生的多维推荐系统显示,在比较分析中,它优于两个维度(用户,项目)和三个维度(用户,项目和上下文,或用户)。基于项目和社会关系)的推荐系统,根据评级函数R的值调整和所有变量的相关性。
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引用次数: 4
Automatic Identification of the Lumen Border in Intravascular Ultrasound Images 血管内超声图像中腔腔边界的自动识别
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.201
JunOh Park, ByoungChul Ko, Hee-Jun Park, J. Nam
Accurately segmenting lumen border in intravascular ultrasound images (IVUS) is very important to study vascular wall architecture for diagnosis of the cardiovascular diseases. After each of IVUS image is transformed to a polar coordinated image, initial points are detected using wavelet transform. Then, lumen border is initialized as the set of important points using non parametric probability density function and smoothing function by removing outlier initial points occurred by noises and artifacts. Finally, polynomial curve fitting is applied to obtain real lumen border using filtered important points. The evaluation of proposed method was performed with related method and the proposed method produced accurate lumen contour detection when compared to another method in most types of IVUS images.
在血管内超声图像(IVUS)中准确分割管腔边界对研究血管壁结构对心血管疾病的诊断具有重要意义。将每幅IVUS图像变换为极坐标图像后,利用小波变换检测初始点。然后,利用非参数概率密度函数和平滑函数,通过去除噪声和伪影产生的离群初始点,将流腔边界初始化为重要点的集合;最后,利用滤波后的重要点进行多项式曲线拟合,得到真实的流腔边界。与相关方法进行了评价,与其他方法相比,该方法在大多数类型的IVUS图像中产生了准确的管腔轮廓检测。
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引用次数: 2
Retrieval Model Based on Word Translation Probabilities and the Degree of Association of Query Concept 基于词翻译概率和查询概念关联度的检索模型
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.183
Jun-Gil Kim, Kyung-Soon Lee
One of the major challenge for retrieval performance is the word mismatch between user`s queries and documents in information retrieval. To solve the word mismatch problem, we propose a retrieval model based on the degree of association of query concept and word translation probabilities in translation-based model. The word translation probabilities are calculated based on the set of a sentence and its succeeding sentence pair. To validate the proposed method, we experimented on TREC AP test collection. The experimental results show that the proposed model achieved significant improvement over the language model and outperformed translation-based language model.
在信息检索中,用户查询和文档之间的词不匹配是影响检索性能的主要问题之一。为了解决词错配问题,在基于翻译的模型中,我们提出了一种基于查询概念关联度和词翻译概率的检索模型。单词翻译概率是基于一个句子及其后续句子对的集合来计算的。为了验证所提出的方法,我们在TREC AP测试集上进行了实验。实验结果表明,该模型在语言模型的基础上取得了显著的进步,优于基于翻译的语言模型。
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引用次数: 0
Gaussian Interpolation-Based Pedestrian Tracking in Continuous Free Spaces 连续自由空间中基于高斯插值的行人跟踪
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.177
Incheol Kim, Eunmi Choi, Huikyung Oh
We propose effective motion and observation models for the position of a WiFi-equipped smartphone user in large indoor environments. Three component motion models provide better proposal distribution of the pedestrian`s motion. Our Gaussian interpolation-based observation model can generate likelihoods at locations for which no calibration data is available. These models being incorporated into the particle filter framework, our WiFi fingerprint-based localization algorithm can track the position of a smartphone user accurately in large indoor environments. Experiments carried with an Android smartphone in a multi-story building illustrate the performance of our WiFi localization algorithm.
我们提出了有效的运动和观察模型,用于在大型室内环境中配备wifi的智能手机用户的位置。三分量运动模型提供了更好的行人运动建议分布。我们基于高斯插值的观测模型可以在没有校准数据的位置产生似然。将这些模型整合到粒子滤波框架中,我们基于WiFi指纹的定位算法可以在大型室内环境中准确跟踪智能手机用户的位置。用Android智能手机在多层建筑中进行的实验验证了我们的WiFi定位算法的性能。
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引用次数: 0
Query Expansion Based on Word Graphs Using Pseudo Non-Relevant Documents and Term Proximity 基于伪非相关文档和词邻近度的词图查询扩展
Pub Date : 2012-06-30 DOI: 10.3745/KIPSTB.2012.19B.3.189
Seung-Hyeon Jo, Kyung-Soon Lee
In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.
本文提出了一种基于词图的伪相关和伪不相关文档的查询扩展方法,以提高信息检索的性能。当文档包含通过查询词组合和查询词接近度提取的核心查询词时,将最初检索到的文档分类到核心集群中。否则,文档将被划分为非核心集群。属于核心查询集群的文档可以看作是伪相关文档,而属于非核心集群的文档可以看作是伪不相关文档。每个聚类被表示为一个有节点和边的图。每个节点表示一个词,每个边表示该词与查询词之间的接近度。通过将核心聚类图中的项权重减去非核心聚类图中的项权重来计算项权重。这意味着在非核心聚类图中具有高权重的项不应被视为扩展项。根据项权值选择展开项。在TREC WT10g测试集上的实验结果表明,该方法在平均精度上比语言模型提高了9.4%。
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引用次数: 1
A Study on the Effectiveness of the Lungs Hand Acupuncture Based on Bio Signal Analysis 基于生物信号分析的肺手针刺疗效研究
Pub Date : 2012-04-30 DOI: 10.3745/KIPSTB.2012.19B.2.077
Bong-hyun Kim, Dong-uk Cho
We carried out study to prove effectiveness as stimulating corresponding points to lung in hand to experiment applied analysis parameters for image and audio signals in this paper. To this end we collected facial image and voice before and after stimulating corresponding points to lung in hand to a male 20s 25 people. In addition, we analyzed change color, voice energy and speaking rate of right cheek area corresponding points to lung to suggest the theory of the Oriental medicine diagnosis based on data collected. As a result, after performing hand acupuncture, L value of right cheek area decreased average 2.33 and a value b value increased 0.76, 0.97 on average. In addition, size of voice energy increased average 0.42, speaking rate decreased average 0.07. In other words, effect of lung function was improved using hand acupuncture corresponding points to lung.
本文通过实验应用分析参数对图像和音频信号进行分析,验证了对手肺相应点进行刺激的有效性。为此,我们采集了20 ~ 25岁男性手肺相应点刺激前后的面部图像和声音。此外,我们还分析了右脸颊区域肺对应点的变化颜色、语音能量和说话率,根据收集的数据提出了东方医学诊断的理论。结果表明,手针刺后右颊区L值平均下降2.33,a值b值平均上升0.76,0.97。此外,语音能量大小平均增加0.42,说话速率平均降低0.07。换句话说,用手针刺肺对应点可以改善肺功能的效果。
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引用次数: 0
Implementation of a Single Human Detection Algorithm for Video Digital Door Lock 视频数字门锁单人检测算法的实现
Pub Date : 2012-04-30 DOI: 10.3745/KIPSTB.2012.19B.2.127
Seung-Hwan Shin, Sang-Rak Lee, Han-Go Choi
Video digital door lock(VDDL) system detects people who access to the door and acquires the human image. Design considerations is that current consumption must be minimized by applying fast human detection algorithm because of battery-based operation. Since the digital door lock takes an image through a fixed camera, detection of a person based on background image leads to high degree of reliability. This paper deals with a single human detection algorithm suitable for VDDL with fulfilling these requirements such that it detects a moving object in an image, then identifies whether the object is a person or not using image processing. The proposed image processing algorithm consists of two steps: Firstly, it detects the human image region using both background image and skin color information. Secondly, it identifies the person using polar histogram based on proportional information of human body. Proposed algorithm is implemented in VDDL and is verified the performance through experiments.
视频数字门锁(VDDL)系统检测出入门的人,获取人的图像。设计考虑的是,由于基于电池的操作,必须通过应用快速的人工检测算法来最小化电流消耗。由于数字门锁是通过固定摄像头拍摄图像,因此基于背景图像检测人的可靠性很高。本文研究了一种适合于VDDL的单人检测算法,该算法可以满足这些要求,即检测图像中的运动物体,然后通过图像处理来识别该物体是否是人。本文提出的图像处理算法包括两个步骤:首先,利用背景图像和肤色信息检测人体图像区域;其次,基于人体比例信息,利用极坐标直方图进行人物识别;在VDDL中实现了该算法,并通过实验验证了算法的性能。
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引用次数: 0
Enhancement of Stereo Feature Matching using Feature Windows and Feature Links 利用特征窗口和特征链接增强立体特征匹配
Pub Date : 2012-04-30 DOI: 10.3745/KIPSTB.2012.19B.2.113
Chang-Il Kim, Soon-Yong Park
This paper presents a new stereo matching technique which is based on the matching of feature windows and feature links. The proposed method uses the FAST feature detector to find image features in stereo images and determines the correspondences of the detected features in the stereo images. We define a feature window which is an image region containing several image features. The proposed technique consists of two matching steps. First, a feature window is defined in a standard image and its correspondence is found in a reference image. Second, the corresponding features between the matched windows are determined by using the feature link technique. If there is no correspondence for an image feature in the standard image, it`s disparity is interpolated by neighboring feature sets. We evaluate the accuracy of the proposed technique by comparing our results with the ground truth of in a stereo image database. We also compare the matching accuracy and computation time with two conventional feature-based stereo matching techniques.
提出了一种基于特征窗和特征链匹配的立体匹配方法。该方法利用FAST特征检测器在立体图像中寻找图像特征,并确定检测到的特征在立体图像中的对应关系。我们定义了一个特征窗口,它是一个包含多个图像特征的图像区域。该方法包括两个匹配步骤。首先,在标准图像中定义特征窗口,并在参考图像中找到对应的特征窗口。其次,利用特征链技术确定匹配窗口之间对应的特征;如果标准图像中没有对应的图像特征,则由相邻的特征集插值其视差。我们通过将我们的结果与立体图像数据库中的地面真实值进行比较来评估所提出技术的准确性。我们还比较了两种传统的基于特征的立体匹配技术的匹配精度和计算时间。
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引用次数: 0
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The Kips Transactions:partb
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