SVM-based ontology matching approach

There are a lot of heterogeneous ontologies in semantic web, and the task of ontology mapping is to find their semantic relationship. There are integrated methods that only simply combine the similarity values which are used in current multi-strategy ontology mapping. The semantic information is not included in them and a lot of manual intervention is also needed, so it leads to that some factual mapping relations are missed. Addressing this issue, the work presented in this paper puts forward an ontology matching approach, which uses multi-strategy mapping technique to carry on similarity iterative computation and explores both linguistic and structural similarity. Our approach takes different similarities into one whole, as a similarity cube. By cutting operation, similarity vectors are obtained, which form the similarity space, and by this way, mapping discovery can be converted into binary classification. Support vector machine (SVM) has good generalization ability and can obtain best compromise between complexity of model and learning capability when solving small samples and the nonlinear problem. Because of the said reason, we employ SVM in our approach. For making full use of the information of ontology, our implementation and experimental results used a common dataset to demonstrate the effectiveness of the mapping approach. It ensures the recall ration while improving the quality of mapping results.     

韩国语连接词尾“■”和“■”的汉语对应研究

连接词尾“■”和“■”的语义及用法较为复杂。本文分析了“■”和“■”的各类语义特征,将这些语义分别与汉语中的表现形式一一进行对应,为韩语学习者攻克这一难点语法提供解决思路,并给出帮助习得连接词尾的建议。     

基于语义分析的设计实体智能搜索

本文提出了在设计联盟组织过程中实现互联网上设计实体智能搜索的方法。根据对互联网上设计实体搜索问题的分析建立了设计实体智能搜索策略；定义了提取设计实体查询向量和描述向量的语义分析规则；提出了基于语义分析的设计实体智能搜索算法；最后编程实现了各项功能。     

An architectural design for effective information retrieval in semantic web

The current web IR system retrieves relevant information only based on the keywords which is inadequate for that vast amount of data. It provides limited capabilities to capture the concepts of the user needs and the relation between the keywords. These limitations lead to the idea of the user conceptual search which includes concepts and meanings. This study deals with the Semantic Based Information Retrieval System for a semantic web search and presented with an improved algorithm to retrieve the information in a more efficient way.This architecture takes as input a list of plain keywords provided by the user and the query is converted into semantic query. This conversion is carried out with the help of the domain concepts of the pre-existing domain ontologies and a third party thesaurus and discover semantic relationship between them in runtime. The relevant information for the semantic query is retrieved and ranked according to the relevancy with the help of an improved algorithm. The performance analysis shows that the proposed system can improve the accuracy and effectiveness for retrieving relevant web documents compared to the existing systems.     

Synthesis and thermal properties of block copolyetheresters with poly(pentamethylene p,p′-bibenzoate) segments

The block copolyetheresters with hard segments of poly(pentamethylene p,p-bibenzoate) and soft segments of poly (tetramethylene ether) were prepared by melt polycondensation of dimethyl-p,p-bibenzoate, 1,5-pentanediol and poly (tetramethyene ether) glycol (PTMEG) with molecular weights of 650, 1000 and 2000. The results by NMR indicate that the polymer composition is determined by the charge molar ratio (x) of PTMEG to dimethyl-p,p-bibenzoate. The thermal transitions of the block copolyetheresters were investigated by DSC in combination with X-ray diffraction and polarized microscopy. Some block copolyetheresters exhibit a monotropic smectic phase due to the presence of the poly (pentamethylene p,p-bibenzoate) segments. As the molar content of PTMEG increases, the average sequence length of the polyester segments decreases, the isotropic-smectic transition temperature and the smectic order decrease accordingly. When x is as high as 0.3, the block copolyetheresters exhibit no liquid crystallinity.     

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

We propose an efficient technique for improving the performance of automatic and cooperative compositions in unstructured Peer-to-Peer networks during service discovery. The technique exploits a probabilistic forwarding algorithm that uses different sources of knowledge, such as network density and service grouping, to reduce the amount of messages exchanged in the network. The technique, analysed in several network configurations by using a simulator to observe resolution time, recall and message overhead, presents good performance especially in dense and large-scale service networks.     

Correlation between crystallization kinetics and melt phase behavior of crystalline-amorphous block copolymer/homopolymer blends

We show that the phase behavior of the strongly segregated blend consisting of a crystalline-amorphous diblock copolymer (C-b-A) and an amorphous homopolymer (h-A), which depends on the degree of wetting of A blocks by h-A, can be probed by the crystallization kinetics of the C block. A lamellae-forming poly(ethylene oxide)-block-polybutadiene (PEO-b-PB) was blended with PB homopolymers (h-PB) of different molecular weights to yield the blends exhibiting ‘wet brush’, ‘partially dry brush’, and ‘dry brush’ phase behavior in the melt state. The crystallization rate of the PEO blocks upon subsequent cooling, as manifested by the freezing (crystallization) temperature (T_f), was highly sensitive to the morphology and spatial connectivity of the microdomains governed by the degree of wetting of PB blocks. As the weight fraction of h-PB reached 0.48, for instance, T_f experienced an abrupt rise as the system entered from the wet-brush to the dry-brush regime, because the crystallization in the PEO cylindrical domains in the former required very large undercooling due to a homogeneous nucleation-controlled mechanism while the process could occur at the normal undercooling in the latter since PEO domains retained lamellar identity with extended spatial connectivity. Our results demonstrate that as long as the C block is present as the minor constituent the melt phase behavior of C-b-A/h-A blends can also be probed using a simple cooling experiment operated under differential scanning calorimetry (DSC).     

复杂断块油田特高含水期实现持续稳产的做法

胜利油田临盘采油厂目前开发动用临盘、商河、临南三个油田,区域构造位于渤海湾盆地济阳坳陷惠民凹陷中央隆起带。“九五”末期由于油田相继进入特高含水期,剩余油分布复杂、断块破碎、油水井套损严重、注采完善程度低,造成油田产量连续三年下降。针对严峻的开发形势,进入“十五”以后,通过深化油藏构造、储层、剩余油潜力的研究,强化注采井网的完善。提高了水驱控制程度,增强油田稳产基础,提高采收率。全厂连续三年原油年产量连续稳定在163×104t,取得较好的开发效果和经济效益。     

BiOSS: A system for biomedical ontology selection

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service.