【文章內(nèi)容簡介】 , Simple Object Access Protocol (SOAP) , SOAP/ 2021. [17] D. Martin et al., OWLS Draft Release, owls/[18] T. Andrews et al., Business Process Execution Language for Web Services (BPEL4WS) , wsbpel, 2021. [19] F. Casati, S. Ilnicki and L. Jin, Adaptive and dynamic service position in eflow, Proceedings of 12th Int. Conf. Advanced Information Systems Engineering (CAiSE), Stockholm, Sweden, June 2021. [20] F. Casati, M. Sayal and . Shan, Developing eServices for Composing eServices, Proceedings of 13th Int. Conf. Advanced Information Systems Engineering (CAiSE), Interlaken, Switzerland, June 2021. [21] H. Schuster, D. Geakopoulos, A. Cichocki and D. Baker, Modeling and posing servicebased and reference processbased multienterprise processes, Proceedings of 12th Int. Conf. Advanced Information Systems Engineering (CAiSE), Stockholm, Sweden, June 2021. [22] A. Hibner and K. Zielinski, Semanticbased dynamic service position and adaptation, Proceedings of IEEE SCW, 2021. [23] S. R. Ponnekanti and A. Fox, SWORD: A developer toolkit for Web service position, Proceedings of 11th World Wide Web Conference, Honolulu, Hawaii, 2021. [24] D. B. Claro, P. Albers and . Hao, A framework for automatic position of RFQ Web services, Proceedings of IEEE SCW, 2021. [25] S. McIlraith and T. C. Son, Adapting golog for position of semantic Web services, Proceedings of 8th Int. Conf. on Knowledge Representation and Reasoning (KR2021), Toulouse, France, April 2021. [26] and P. . Sheu, Relational service position, submitted to IEEE Trans Data and Knowledge Engineering, 2021. 394 P. . Sheu amp。 C. V. Ramamoorthy [27] P. . Sheu, SCDL for different problems, technical report, Department of EECS, University of California, Irvine, 2021. [28] P. . Sheu, A. Kitazawa, C. Ishi, K. Kaneko and F. Xie, From SemanticObjects to structured natural language, Int. J. Semantic Computing 1(3) (2021) 359–375. [29] P. . Sheu and A. Kitazawa, From SemanicObjects to semantic software engineering, Int. J. Semantic Computing 1(1) (2021) 11–28. [30] N. J. Nilsson, Artificial Intelligence — A New Synthesis (Man Kaufmann, 1998). （附件 4：外文原文二） International Journal of Semantic Computing Vol. 3, No. 3 (2021) 383–394 169。World Scientific Publishing Company PROBLEMS, SOLUTIONS, AND SEMANTIC COMPUTING PHILLIP . SHEU? ,? and C. V. RAMAMOORTHY? ,? ? Institute for Semantic Computing ?University of California, Irvine ?University of California, Berkeley Semantic Computing extends Semantic Web both in breadth and depth. It bridges, and integrates, several puting technologies into a plete and unified theme. This article discusses the essences of Semantic Computing with a description of SemanticServices. Net, a new paradigm that enables ―Problemdriven‖ search that may offer a new story to the Inter. Keywords: Semantic puting。 search engine。 problem solving. 1. Problems and Solutions The mercial world is mostly about demands and supplies. In most cases demands trigger supplies, and in some cases supplies create demands. A more general concept for needs may be problems, and that for supplies may be solutions. The Inter has provided a global infrastructure to connect problems with solutions. For example eBay has done a great job on auctions. A keywordbased search engine such as Google may be considered as a special problem solver that solves the problem: Find (Web) documents that contain the keywords provided by the user. A Question/Answering (Qamp。A) system (., [3]) may be considered as another special problem solver that solves the problem: Find answers for the question (based on the documents collected by the system). Both keywordbased search engines and Qamp。A system have done an excellent job for the problems they try to solve. But from the view point of Problem Solving, they are far from being sufficient. It can be easily seen that not every problem falls into the two general categories we talked about. Any puter scientist may easily e up the following list: (1) Computational Problems and other Mathematical Problems. Solving such problems require putation to be involved. Some initial attempts have been made (., Wolfram|Appha, but lots more need to be done in this space. 383 384 P. . Sheu amp。 C. V. Ramamoorthy (2) Database Search Problems such as Find the supermarkets carrying apples at less than 2 dollars a pound. Deep webs usually work by themselves and they are not connected (not because they cannot be, but perhaps because they do not want to be). (3) Synthesis Problems such as Build a program that takes a set of numbers and returns them in increasing order. Automatic synthesis in general in hard and remains to be a goal to be acplished. (4) Reasoning Problems such as What can be derived from this set of facts? Like automatic synthesis, automatic reasoning may be hard. (5) Data Analysis Problems such as What are the mon patterns shown in this set of images? There are a lot of approaches we may take to solve this problem。 but this is not a problem addressed by search engines or Qamp。A systems. (6) “Personal” Problems such as I know person A and person B but they don?t like each other, how can I put them to work? This may not be a scientific problem and its solution may very much reply on experiences, social considerations, etc. Our main point is not to classify all the problems. What actually interests us is matching problems with solutions. The Inter does provide us with an infrastructure to connect problems and solutions, but we may have not fully utilized this infrastructure. So far it has been useful for trading. If we can extend the concept of trading from goods to problems and buyers to solutions, we may have a new story for the Inter. 2. Bridging Problems and Solutio