We present an approach for automatically learning paraphrases from aligned monolingual corpora. Our algorithm works by generalizing the syntactic paths between corresponding anchors in aligned sentence pairs. Compared to previous work, structural paraphrases generated by our algorithm tend to be much longer on average, and are capable of capturing long-distance dependencies. In addition to a standalone evaluation of our paraphrases, we also describe a question answering application currently under development that could immensely benefit from automatically-learned structural paraphrases.
Abstract. Because Remote Procedure Calls do not compose efficiently, designers of distributed object systems use Data Transfer and Remote Façade patterns to create large-granularity interfaces, hard-coded for particular client use cases. As an alternative to RPC-based distributed objects, this paper presents Remote Batch Invocation (RBI), language support for explicit client-defined batches. A Remote Batch statement combines remote and local execution: all the remote code is executed in a single round-trip to the server, where all data sent to the server and results from the batch are communicated in bulk. RBI supports remote blocks, iteration and conditionals, and local handling of remote exceptions. RBI is efficient even for fine-grained interfaces, eliminating the need for hand-optimized server interfaces. We demonstrate RBI with an extension to Java, using RMI internally as the transport layer. RBI supports large-granularity, stateless server interactions, characteristic of service-oriented computing.
Abstract. Object persistence architectures support transparent access to persistent objects. For efficiency, many of these architectures support queries that can prefetch associated objects as part of the query result. While specifying prefetch manually in a query can significantly improve performance, correct prefetch specifications are difficult to determine and maintain, especially in modular programs. Incorrect prefetching is difficult to detect, because prefetch is only an optimization hint. This paper presents AutoFetch, a technique for automatically generating prefetch specifications using traversal profiling in object persistence architectures. AutoFetch generates prefetch specifications based on previous executions of similar queries. In contrast to previous work, AutoFetch can fetch arbitrary traversal patterns and can execute the optimal number of queries. AutoFetch has been implemented as an extension of Hibernate. We demonstrate that AutoFetch improves performance of traversals in the OO7 benchmark and can automatically predict prefetches that are equivalent to hand-coded queries, while supporting more modular program designs.
Jambi Education Office, is a government institution located in the city of Jambi which is one of the government institutions engaged in education. It serves all existing schools in Jambi. In the process of selecting the best schools, there are many obstacles facing the educators; the condition of the building and the facilities at the school. This happens because of the number of schools located in Jambi. Therefore, not all schools will be the best schools; only those which meet the criteria will be the best school. It can be done by through the processing of decision support system using a method called Simple Additive Weighting. This system can be used to determine which schools are eligible to be the best schools in Jambi. The utilization of decision support system with Simple Additive Weighting method can determine the weight value for each attribute, then proceed with a ranking process that will select the best alternative from a number of alternatives. In this case, the intended alternative is the right ones to become the best schools based on the specified criteria.
Transparent persistence promises to integrate programming languages and databases by allowing programs to access persistent data with the same ease as non-persistent data.In this work we demonstrate the feasibility of optimizing transparently persistent programs by extracting queries to efficiently prefetch required data. A static analysis derives query structure and conditions across methods that access persistent data. Using the static analysis, our system transforms the program to execute explicit queries. The transformed program composes queries across methods to handle method calls that return persistent data. We extend an existing Java compiler to implement the static analysis and program transformation, handling recursion and parameterized queries. We evaluate the effectiveness of query extraction on the OO7 and TORPEDO benchmarks. This work is focused on programs written in the current version of Java, without languages changes. However, the techniques developed here may also be of value in conjunction with object-oriented languages extended with high-level query syntax.
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