Business Process Retrieval Based on Behavioral Semantics

This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie

Term Extraction and Disambiguation for Semantic Knowledge Enrichment: A Case Study on Initial Public Offering (IPO)

Domain knowledge bases are a basis for advanced knowledge-based systems, manually creating a formal knowledge base for a certain domain is both resource consuming and non-trivial. In this paper, we propose an approach that provides support to extract, select, and disambiguate terms embedded in domain specific documents. The extracted terms are later used to enrich existing ontologies/taxonomies, as well as to bridge domain specific knowledge base with a generic knowledge base such as WordNet. The proposed approach addresses two major issues in the term extraction domain, namely quality and efficiency. Also, the proposed approach adopts a feature-based method that assists in topic extraction and integration with existing ontologies in the given domain. The proposed approach is realized in a research prototype, and then a case study is conducted in order to illustrate the feasibility and the efficiency of the proposed method in the finance domain. A preliminary empirical validation by the domain experts is also conducted to determine the accuracy of the proposed approach. The results from the case study indicate the advantages and potential of the proposed approach

Semantic-Based Publish/Subscribe System in Social Network

The publish/subscribe model has become a prevalent paradigm for building distributed notification services by decoupling the publishers and the subscribers from each other. The semantics-based publish/subscribe system allows highly expressive descriptions of subscriptions and publications and thus is more appropriate for content dissemination when a finer level of granularity is necessary. In this paper we have designed and implemented a semantic-based publish/subscribe system that can be adapted into social networks where thousands of people can share their common interests through publications and subscriptions. We have described our ontology, defined publishers’ and subscribers’ data semantics or schema, provided a matching algorithm, portrayed the implementation and shown the result of an implemented publish/subscribe system that allows the users to publish and subscribe different kinds of news in a social network platform. Our experience shows that the semantic-based publish/subscribe system can enhance the current social networks by providing an effective content dissemination mechanism

Phương pháp phát hiện dịch vụ Web ngữ nghĩa và ứng dụng trong cộng tác doanh nghiệp

Tích hợp doanh nghiệp (Business to Business integration - B2Bi) là kết nối các chức năng kinh doanh của doanh nghiệp thường bị phân tán trên các hệ khác nhau nhằm thực thi một tiến trình nghiệp vụ nào đó. Các hệ thống chức năng này được mô tả dưới dạng các dịch vụ dựa trên các chuẩn biểu diễn ngữ nghĩa nên giúp cho quá trình phát hiện các chức năng liên quan đến cùng một lĩnh vực kinh doanh có sự chính xác hơn. Một trong những vấn đề quan trọng của quá trình tích hợp các doanh nghiệp ở mức thực thi của quy trình nghiệp vụ cộng tác là xây dựng các phương pháp phát hiện các dịch vụ Web (Web Services-WS) cùng mô tả về lĩnh vực kinh doanh có liên quan với nhau giữa các doanh nghiệp. Như vậy, mục tiêu của bài báo là xây dựng phương pháp phát hiện WS (Web Services Discovery) từ danh sách các dịch vụ Web quảng cáo mà tương đồng với WS mẫu với một ngưỡng α cho trước

Business Process Retrieval Based on Behavioral Semantics

This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called “BeMantics” for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The “BeMantics” framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics properties

Personalizing a Concept Similarity Measure in the Description Logic ELH with Preference Profile

Concept similarity measure aims at identifying a degree of commonality of two given concepts and is often regarded as a generalization of the classical reasoning problem of equivalence. That is, any two concepts are equivalent if and only if their similarity degree is one. However, existing measures are often devised based on objective factors, e.g. structural-based measures and interpretation-based measures. When these measures are employed to characterize similar concepts in an ontology, they may lead to unintuitive results. In this work, we introduce a new notion called concept similarity measure under preference profile with a set of formally defined properties in Description Logics. This new notion may be interpreted as measuring the similarity of two concepts under subjective factors (e.g. the agent's preferences and domain-dependent knowledge). We also develop a measure of the proposed notion and show that our measure satisfies all desirable properties. Two algorithmic procedures are introduced for top-down and bottom-up implementation, respectively, and their computational complexities are intensively studied. Finally, the paper discusses the usefulness of the approach to potential use cases

Algorithms for Measuring Similarity Between ELH Concept Descriptions: A Case Study on Snomed ct

In Description Logics, subsumption is regarded as one of the most prominent reasoning services. It checks, relative to the logical definitions in the ontology, whether one concept is more general/specific than another. When no subsumption relationship is identified, however, no information about the two concepts can be given. In several realistic Semantic Web applications, knowing the level of similarity between two concepts, though lacking the subsumption relationship, is beneficial. This work introduces a new method for measuring the degree of similarity between two concept descriptions in the DL ELH, despite not being in a subsumption relation. Two algorithms are devised based on the known homomorphism-based structural subsumption characterization. The first algorithm employs the top-down approach, whereas the second is carried out in the reverse direction. A bottom-up algorithm has better efficiency, making it more suitable to large-scale ontologies developed using an inexpressive DL in the EL family, such as the renowned medical ontology Snomed ct. The computational performance of the proposed measure is intensively studied, and interesting findings in Snomed ct are reported

Tích hợp ontology với tiếp cận lý thuyết đồng thuận

The reuse of ontology has been an important factor in developing shared knowledge on the Semantic Web. However, this cannot completely reduce conflict potentials in knowledge bases. In the ontology integration process on the concept level, we need to determine the domain and range ofproperties of integrating ontologies. This paper presents an algorithm for ontology integration on concept level based on the consensus theory and an evaluation function of a similarity measure between concepts in its hierarchical structure. This paper also proves that the consensus theory is a useful tool for building collective knowledge from different sources.World Wide Web (WWW) phát triển nhằm cho phép con người có thể chia sẻ thông tin với nhau thông qua môi trường phân tán. Nhằm đáp ứng nhu cầu sử dụng dịch vụ ngày càng cao thì dịch vụ Web là nơi hỗ trợ khả năng tương tác giữa các ứng dụng trên các máy tính khác nhau thông qua môi trường Internet và sự gắn kết giữa chúng được mô tả bằng ngôn ngữ XML. Cùng sự phát triển của Web ngữ nghĩa với mục đích nâng cao hiệu quả của Web hiện tại, số lượng các Ontology do các cá nhân, tổ chức nghiên cứu, doanh nghiệp tạo ra ngày càng trở nên phong phú và đa dạng hơn. Tích hợp các Ontology từ các nguồn trên nhằm mang lại lợi ích trong quá trình hợp tác, đồng thời khám phá ra các dịch vụ Web ngữ nghĩa phù hợp với yêu cầu ban đầu của người sử dụng. Có nhiều cách tiếp cận cho bài toán tích hợp ontology, bài báo tập trung nghiên cứu theo hướng tiếp cận thông minh trong tích hợp ontology bằng cách sử dụng lý thuyết đồng thuận – một phương pháp tiếp cận mới giúp quá trình khám phá, biên tập dịch vụ Web một cách tự động và thông minh hơn