长尾理论视角下基于DCA 的网络自助出版推荐系统

随着自助出版系统文本规模的迅速增长,选用合理的推荐技术有利于＂长尾＂文本的发掘和价值实现。针对自助出版文本,设计了基于有向图的聚类算法DCA（Directed Graph Clustering Algorithm）,将聚类看成是确定对象的过程,根据词间信息传递量的大小选定特征词集对文本进行聚类。为改善＂长尾＂文本聚类的有效性,文中所述系统设置了浮动相似度阙值及推荐公共池。实验结果表明,较之K-Means算法,该算法有较强的自适应性和通用性,能有效地运用到自助出版文本的个性化推荐系统领域。     

AFEW-VA database for valence and arousal estimation in-the-wild

Continuous dimensional models of human affect, such as those based on valence and arousal, have been shown to be more accurate in describing a broad range of spontaneous, everyday emotions than the more traditional models of discrete stereotypical emotion categories (e.g. happiness, surprise). However, most prior work on estimating valence and arousal considered only laboratory settings and acted data. It is unclear whether the findings of these studies also hold when the methodologies proposed in these works are tested on data collected in-the-wild. In this paper we investigate this. We propose a new dataset of highly accurate per-frame annotations of valence and arousal for 600 challenging video clips extracted from feature films (also used in part for the AFEW dataset). For each video clip, we further provide per-frame annotations of 68 facial landmarks. We subsequently evaluate a number of common baseline and state-of-the-art methods on both a commonly used laboratory recording dataset (Semaine database) and the newly proposed recording set (AFEW-VA). Our results show that geometric features perform well independently of the settings. However, as expected, methods that perform well on constrained data do not necessarily generalise to uncontrolled data and vice-versa.     

促进中国微电脑企业发展的新思路

从电脑硬件和软件两个方面阐述了中国微电脑企业生存与发展的途径和方式，强调要提 高硬件产品质量和技术水平，加强软件产业化。     

Empirical study of constructing a knowledge organization system of patent documents using topic modeling

A knowledge organization system (KOS) can help easily indicate the deep knowledge structure of a patent document set. Compared to classification code systems, a personalized KOS made up of topics can represent the technology information in a more agile, detailed manner. This paper presents an approach to automatically construct a KOS of patent documents based on term clumping, Latent Dirichlet Allocation (LDA) model, K-Means clustering and Principal Components Analysis (PCA). Term clumping is adopted to generate a better bag-of-words for topic modeling and LDA model is applied to generate raw topics. Then by iteratively using K-Means clustering and PCA on the document set and topics matrix, we generated new upper topics and computed the relationships between topics to construct a KOS. Finally, documents are mapped to the KOS. The nodes of the KOS are topics which are represented by terms and their weights and the leaves are patent documents. We evaluated the approach with a set of Large Aperture Optical Elements (LAOE) patent documents as an empirical study and constructed the LAOE KOS. The method used discovered the deep semantic relationships between the topics and helped better describe the technology themes of LAOE. Based on the KOS, two types of applications were implemented: the automatic classification of patents documents and the categorical refinements above search results.     

On measuring the distance between histograms

A distance measure between two histograms has applications in feature selection, image indexing and retrieval, pattern classification and clustering, etc. We propose a distance between sets of measurement values as a measure of dissimilarity of two histograms. The proposed measure has the advantage over the traditional distance measures regarding the overlap between two distributions; it takes the similarity of the non-overlapping parts into account as well as that of overlapping parts. We consider three versions of the univariate histogram, corresponding to whether the type of measurement is nominal, ordinal, and modulo and their computational time complexities are Θ(b), Θ(b) and O(b²) for each type of measurements, respectively, where b is the number of levels in histograms.     

MSRT: multi-scale representation transformer for regression-based human pose estimation

Pattern Analysis and Applications - In this paper, we are interested in the human pose estimation problem with a focus on leveraging discriminative pose features. Recent pose estimation works...