基于微博用户兴趣话题的相似用户挖掘

相似用户挖掘是提高社交网络服务质量的重要途径，在面向大数据的社交网络时代，准确的相似用户挖掘对于用户和互联网企业等都有重要的意义，而根据用户自己的兴趣话题挖掘的相似用户更符合相似用户的要求。提出了一种基于用户兴趣话题进行相似用户挖掘的方法。该方法首先使用TextRank话题提取方法对用户进行兴趣话题提取，再对用户发表内容进行训练，计算出所有词之间的相似度。提出CP（Corresponding Position similarity）、CPW（Corresponding Position Weighted similarity）、AP（All Position similarity）、APW（All Position Weighted similarity）四种用户兴趣话题词相似度计算方法，通过用户和相似用户间关注、粉丝重合率验证相似用户挖掘效果，APW similarity的相似用户的关注/粉丝重合百分比为1.687%，优于提出的其他三种算法，分别提高了26.3%、2.8%、12.4%，并且比传统的文本相似度方法Jaccard相似度、编辑距离算法、余弦相似度分别提高了20.4%、21.2%、45.0%。因此APW方法可以更加有效地挖掘出用户的相似用户。     

Container-based cluster orchestration systems: A taxonomy and future directions

Containers, enabling lightweight environment and performance isolation, fast and flexible deployment, and fine-grained resource sharing, have gained popularity in better application management and deployment in addition to hardware virtualization. They are being widely used by organizations to deploy their increasingly diverse workloads derived from modern-day applications such as web services, big data, and internet of things in either proprietary clusters or private and public cloud data centers. This has led to the emergence of container orchestration platforms, which are designed to manage the deployment of containerized applications in large-scale clusters. These systems are capable of running hundreds of thousands of jobs across thousands of machines. To do so efficiently, they must address several important challenges including scalability, fault tolerance and availability, efficient resource utilization, and request throughput maximization among others. This paper studies these management systems and proposes a taxonomy that identifies different mechanisms that can be used to meet the aforementioned challenges. The proposed classification is then applied to various state-of-the-art systems leading to the identification of open research challenges and gaps in the literature intended as future directions for researchers.     

Taxonomy of digital community currency platforms*

ABSTRACT

Community currencies are used to pay for products or services within specific groups defined by geographical boundaries or specific common interests. Financial crises, social emergence in developing countries, and increased access to digital devices have stimulated a growing number of communities worldwide to develop digital currency projects. These projects use technologies ranging from traditional plastic cards to mobile phones and blockchain technologies. Following the design science research approach, this paper analyzes digital community currencies (DCCs) by developing a taxonomy based on platform architecture, governance, transactionality and virtuality. By investigating 22 DCC platforms around the world, 4 groups were distinguished: local, proprietary, commons and cyber. The identification of these four different groups of digital community currencies allows us to better discuss the potentials and limitations of each one of them. The presented taxonomy can be useful to researchers and practitioners both to explain and to design DCC platforms. Discussing each of the emerging categories from the proposed taxonomy helps us to provide insights into DCCs, offering a new theoretical frame for investigating the particular case of digital payment platforms.     

多特征融合的兴趣点推荐算法

基于位置社交网络的兴趣点推荐越来越受到工业界和学术界的关注。由于用户签到数据集的稀疏性以及签到地理位置的聚集性，使得目前的推荐算法效率普遍不高，特别是当用户外出到新的地点时，推荐效果更是急剧下降。因此本文提出了一种基于用户-区域-内容主题的多特征联合推荐算法（UCRTM），以隐主题模型为基础，在统一的框架下利用隐含因子关联性融合了用户的偏好、兴趣点的内容以及兴趣点所属地理区域主题等信息来进行推荐，使得用户无论身处何地，都能获得理想的推荐服务。本文在两种真实的数据集上进行了实验，结果表明该方法不仅能够克服数据的稀疏性以及弱语义性等问题，而且与其他方法相比具有更高的推荐准确率。     

A Survey of Underwater Multi-Robot Systems

As a cross-cutting field between ocean development and multi-robot system (MRS), the underwater multi-robot system (UMRS) has gained increasing attention from researchers and engineers in recent decades. In this paper, we present a comprehensive survey of cooperation issues, one of the key components of UMRS, from the perspective of the emergence of new functions. More specifically, we categorize the cooperation in terms of task-space, motion-space, measurement-space, as well as their combination. Further, we analyze the architecture of UMRS from three aspects, i.e., the performance of the individual underwater robot, the new functions of underwater robots, and the technical approaches of MRS. To conclude, we have discussed related promising directions for future research. This survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.      

Taxonomic importance of pollen morphology in Veratrum L. (Melanthiaceae) using microscopic techniques

Previous studies reported that intrageneric relationships of genus Veratrum of family Melanthiaceae are controversial and hard to delimit. Therefore, we observed the pollen morphological features of six species in the genus Veratrum in detail using both light microscopy and scanning electron microscopy and investigated their significance for Veratrum taxonomy. Among them, five were studied for the first time. The results demonstrated that pollen grains of Veratrum are medium in size with P/E being 0.31–0.60. Three types of shape in polar view have been observed elliptic, long‐elliptic, or wide‐elliptic with blunt or rounded at both ends. Two types of width of colpus reported narrow or wide, two types of depth of colpus reported deep or flat, and two types of length of colpus reported extend almost or do not extend to the ends, whereas two types of colpus membranes reported absent or obvious. One type of surface ornamentation was noted as reticulate. These results support species Veratrum album and Veratrum lobelianum as well as Veratrum grandiflorum and Veratrum oxysepalum as two independent species, respectively, rather than classifying Veratrum into two sections. Overall, we demonstrated that the ratio of polar axis length to equatorial axial length, pollen characteristics at the polar view, the colpus morphology, and the surface ornamentation of pollen grains of genus Veratrum have important systematic significance in identification and delimitation of species.     

Feature-based ontological framework for semantic interoperability in product development

An essential requirement in integrating tasks in product development is to have a seamless exchange of product information through the entire product lifecycle. A key challenge in the integration is the exchange of shape semantics in terms of understandable labels and representations. A unified taxonomy is proposed to represent, classify, and extract shape features. This taxonomy is built using the Domain-Independent Form Feature (DIFF) model as the representation of features. All the shape features in a product model are classified under three main classes, namely, volumetric features, deformation features and free-form surface features. Shape feature ontology is developed using the unified taxonomy, which brings the shape features under a single reasoning framework. One-to-many reasoning framework is presented for mapping semantically equivalent information (label and representation) of the feature to be exchanged to target applications, and the reconstruction of the shape model automatically in that target application. An algorithm has been developed to extract the semantics of shape features and construct the model in the target application. The algorithm developed has been tested for shape models taken from literature and test cases are selected based on variations of topology and geometry. Results of exchanging product information are presented and discussed. Finally, the limitations of the proposed method for exchanging product information are explained.     

ED-SWE: Event detection based on scoring and word embedding in online social networks for the internet of people

Online social media networks are gaining attention worldwide, with an increasing number of people relying on them to connect, communicate and share their daily pertinent event-related information. Event detection is now increasingly leveraging online social networks for highlighting events happening around the world via the Internet of People. In this paper, a novel Event Detection model based on Scoring and Word Embedding (ED-SWE) is proposed for discovering key events from a large volume of data streams of tweets and for generating an event summary using keywords and top-k tweets. The proposed ED-SWE model can distill high-quality tweets, reduce the negative impact of the advent of spam, and identify latent events in the data streams automatically. Moreover, a word embedding algorithm is used to learn a real-valued vector representation for a predefined fixed-sized vocabulary from a corpus of Twitter data. In order to further improve the performance of the Expectation-Maximization (EM) iteration algorithm, a novel initialization method based on the authority values of the tweets is also proposed in this paper to detect live events efficiently and precisely. Finally, a novel automatic identification method based on the cosine measure is used to automatically evaluate whether a given topic can form a live event. Experiments conducted on a real-world dataset demonstrate that the ED-SWE model exhibits better efficiency and accuracy than several state-of-art event detection models.     

Morphological description of the immature stages of Hermetia illucens (Linnaeus, 1758) (Diptera: Stratiomyidae)

In the dipteran genus Hermetia, only 6 of the 78 valid species have documented immature stages: H. albitarsis Fabricius, 1805, H. aurata Bellardi, 1859, H. concinna Williston, 1900, H. illucens (Linnaeus, 1758), H. panamensis Greene, 1940 and H. pulchra Weidemann, 1830. In particular, H. illucens stands out due to its reported applicability for forensic, medical and economic purposes. Here, we described the morphology of eggs and immature stages of this species, with a view to detecting differences between instars and in the pupal stage, which should eventually help properly identifying larval age. We utilized both optical and scanning electron microscopy tools. The eggs are elliptical and elongated, and color varies from cream white to yellowish. The larvae are apodal, hemichephalic and holopneustic, flattened dorso‐ventrally and may be recognized by the head elongated, dorsal and ventral chaetotaxy of the cephalic capsule, thoracic and abdominal segments, and the morphology of the anterior and posterior spiracles. The pupae are adecticous and coarctate, tegument dark brown and pruinescence varying from brown to golden. The overall morphology across instars is similar, but marked variations were observed in the shape of the antennal articuli and the shape of the setae (first instar compared to the others). Our results supplement the biological information on Hermetia illucens and should aid the proper identification and aging of juveniles in the field, as a way to minimize errors in the calculation of the post‐mortem interval.     

Spores morphology of the family Pteridaceae from Shandong Province,China

In this article, we explored systematically the spore morphology of Pteridaceae by observation of the species distributed in Shandong Province using scanning electron microscopy (SEM). The results showed that the spore morphology of all the species in the family is tetrahedral and trilete. The characters of spore ornamentation are intraspecies stable, but significantly different among species and genera. Spore morphology is significant in exploring the phylogenetic relationships of Pteridaceae as well as in generic and specific delimitations.