XML keyword search with promising result type recommendations

Keyword search enables inexperienced users to easily search XML database with no specific knowledge of complex structured query languages and XML data schemas. Existing work has addressed the problem of selecting data nodes that match keywords and connecting them in a meaningful way, e.g., SLCA and ELCA. However, it is time-consuming and unnecessary to serve all the connected subtrees to the users because in general the users are only interested in part of the relevant results. In this paper, we propose a new keyword search approach which basically utilizes the statistics of underlying XML data to decide the promising result types and then quickly retrieves the corresponding results with the help of selected promising result types. To guarantee the quality of the selected promising result types, we measure the correlations between result types and a keyword query by analyzing the distribution of relevant keywords and their structures within the XML data to be searched. In addition, relevant result types can be efficiently computed without keyword query evaluation and any schema information. To directly return top-k keyword search results that conform to the suggested promising result types, we design two new algorithms to adapt to the structural sensitivity of the keyword nodes over the keyword search results. Lastly, we implement all proposed approaches and present the relevant experimental results to show the effectiveness of our approach.     

嵌入社会责任的农业企业绩效评价研究

根据现代农业企业的特点和社会对农业企业的要求,认为评价农业企业的绩效,应该将财务指标和非财务指标综合起来加以考量.在明确绩效评价指标原则的基础上,建立了涉及企业财务、客户、内部流程、学习创新和社会责任等5个维度的农业企业绩效评价指标体系.以对丰原生化公司的综合评价为例,介绍了评价指标体系的应用效果.     

ELCA evaluation for keyword search on probabilistic XML data

As probabilistic data management is becoming one of the main research focuses and keyword search is turning into a more popular query means, it is natural to think how to support keyword queries on probabilistic XML data. With regards to keyword query on deterministic XML documents, ELCA (Exclusive Lowest Common Ancestor) semantics allows more relevant fragments rooted at the ELCAs to appear as results and is more popular compared with other keyword query result semantics (such as SLCAs). In this paper, we investigate how to evaluate ELCA results for keyword queries on probabilistic XML documents. After defining probabilistic ELCA semantics in terms of possible world semantics, we propose an approach to compute ELCA probabilities without generating possible worlds. Then we develop an efficient stack-based algorithm that can find all probabilistic ELCA results and their ELCA probabilities for a given keyword query on a probabilistic XML document. Finally, we experimentally evaluate the proposed ELCA algorithm and compare it with its SLCA counterpart in aspects of result probability, time and space efficiency, and scalability.     

Aligning Collaborative Business Processes—An Organization-Oriented Perspective

Business collaboration encompasses the coordination of information flows among organizations as well as the composition of their business processes toward mutual benefits. While integrating business processes of different organizations seamlessly, it brings great challenges to keep participating organizations as autonomous entities. To address this issue, we propose a new perspective on modeling collaborative business processes with a novel concept called relative workflow (RWF). With its visibility control mechanism, the RWF model defines what a participating organization can perceive in collaboration and thereby allows each organization to customize its own collaboration process and behaviors. In this paper, we present a formal definition of RWFs and related algorithms for generating RWFs. A prototype is implemented on the Web service platform for the proof-of-concept purpose.     

Independence of Containing Patterns Property and Its Application in Tree Pattern Query Rewriting Using Views

We show that several classes of tree patterns observe the independence of containing patterns property, that is, if a pattern is contained in the union of several patterns, then it is contained in one of them. We apply this property to two related problems on tree pattern rewriting using views. First, given view V and query Q, is it possible for Q to have an equivalent rewriting using V which is the union of two or more tree patterns, but not an equivalent rewriting which is a single pattern? This problem is of both theoretical and practical importance because, if the answer is no, then, to find an equivalent rewriting of a tree pattern using a view, we should use more efficient methods, such as the polynomial time algorithm of Xu and Özsoyoglu (2005), rather than try to find the union of all contained rewritings (which takes exponential time in the worst case) and test its equivalence to Q. Second, given a set S of views, we want to know under what conditions a subset S′ of S is redundant in the sense that for any query Q, the contained rewritings of Q using the views in S′ are contained in those using the views in S???S′. Solving this problem can help us to, for example, choose the minimum number of views to be cached, or better design the virtual schema in a mediated data integration system, or avoid repeated calculation in query optimization. For the first problem, we identify several classes of tree patterns for which the equivalent rewriting can be expressed as a single tree pattern. For the second problem, we present necessary and sufficient conditions for S′ to be redundant with respect to some classes of tree patterns. For both problems we consider extension to cases where there are rewritings using the intersection of multiple views and/or where a schema graph is present.     

Fabrication of Fe3O4 Dots Embedded in 3D Honeycomb‐Like Carbon Based on Metallo–Organic Molecule with Superior Lithium Storage Performance

A novel metallo–organic molecule, ferrocene, is selected as building block to construct Fe₃O₄ dots embedded in 3D honeycomb‐like carbon (Fe₃O₄ dots/3DHC) by using SiO₂ nanospheres as template. Unlike previously used inorganic Fe₃O₄ sources, ferrocene simultaneously contains organic cyclopentadienyl groups and inorganic Fe atoms, which can be converted to carbon and Fe₃O₄, respectively. Atomic‐scale Fe distribution in started building block leads to the formation of ultrasmall Fe₃O₄ dots (≈3 nm). In addition, by well controlling the feed amount of ferrocene, Fe₃O₄ dots/3DHC with well‐defined honeycomb‐like meso/macropore structure and ultrathin carbon wall can be obtained. Owing to unique structural features, Fe₃O₄ dots/3DHC presents impressive lithium storage performance. The initial discharge and reversible capacities can reach 2047 and 1280 mAh g^?1 at 0.05 A g^?1. With increasing the current density to 1 and 3 A g^?1, remarkable capacities of 963 and 731 mAh g^?1 remain. Moreover, Fe₃O₄ dots/3DHC also has superior cycling stability, after a long‐term charge/discharge for 200 times, a high capacity of 1082 mAh g^?1 can be maintained (80% against the capacity of the 2nd cycle).     

Adaptive relaxation for querying heterogeneous XML data sources

Searching XML data with a structured XML query can improve the precision of results compared with a keyword search. However, the structural heterogeneity of the large number of XML data sources makes it difficult to answer the structured query exactly. As such, query relaxation is necessary. Previous work on XML query relaxation poses the problem of unnecessary computation of a big number of unqualified relaxed queries. To address this issue, we propose an adaptive relaxation approach which relaxes a query against different data sources differently based on their conformed schemas. In this paper, we present a set of techniques that supports this approach, which includes schema-aware relaxation rules for relaxing a query adaptively, a weighted model for ranking relaxed queries, and algorithms for adaptive relaxation of a query and top-k query processing. We discuss results from a comprehensive set of experiments that show the effectiveness and the efficiency of our approach.     

An effective suggestion method for keyword search of databases

This paper solves the problem of providing high-quality suggestions for user keyword queries over databases. With the assumption that the returned suggestions are independent, existing query suggestion methods over databases score candidate suggestions individually and return the top-k best of them. However, the top-k suggestions have high redundancy with respect to the topics. To provide informative suggestions, the returned k suggestions are expected to be diverse, i.e., maximizing the relevance to the user query and the diversity with respect to topics that the user might be interested in simultaneously. In this paper, an objective function considering both factors is defined for evaluating a suggestion set. We show that maximizing the objective function is a submodular function maximization problem subject to n matroid constraints, which is an NP-hard problem. An greedy approximate algorithm with an approximation ratio O(\(\frac {1}{1+n}\)) is also proposed. Experimental results show that our suggestion outperforms other methods on providing relevant and diverse suggestions.