The Experts below are selected from a list of 54 Experts worldwide ranked by ideXlab platform

Xiaofang Zhou - One of the best experts on this subject based on the ideXlab platform.

  • webput a web aided data imputation system for the general type of missing String Attribute values
    International Conference on Data Engineering, 2019
    Co-Authors: Shuangli Shan, Qiang Yang, Jia Zhu, Mohamed A Sharaf, Xiaofang Zhou
    Abstract:

    In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.

  • ICDE - WebPut: A Web-Aided Data Imputation System for the General Type of Missing String Attribute Values
    2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019
    Co-Authors: Shuangli Shan, Qiang Yang, Jia Zhu, Mohamed A Sharaf, Li Yang, Xiaofang Zhou
    Abstract:

    In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.

  • TRIP: An Interactive Retrieving-Inferring Data Imputation Approach
    IEEE Transactions on Knowledge and Data Engineering, 2015
    Co-Authors: Lu Qin, Hong Cheng, Xiangliang Zhang, Xiaofang Zhou
    Abstract:

    Data imputation aims at filling in missing Attribute values in databases. Most existing imputation methods to String Attribute values are inferring-based approaches, which usually fail to reach a high imputation recall by just inferring missing values from the complete part of the data set. Recently, some retrieving-based methods are proposed to retrieve missing values from external resources such as the World Wide Web, which tend to reach a much higher imputation recall, but inevitably bring a large overhead by issuing a large number of search queries. In this paper, we investigate the interaction between the inferring-based methods and the retrieving-based methods. We show that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. With this intuition, we propose an inTeractive Retrieving-Inferring data imPutation approach (TRIP), which performs retrieving and inferring alternately in filling in missing Attribute values in a data set. To ensure the high recall at the minimum cost, TRIP faces a challenge of selecting the least number of missing values for retrieving to maximize the number of inferable values. Our proposed solution is able to identify an optimal retrieving-inferring scheduling scheme in deterministic data imputation, and the optimality of the generated scheme is theoretically analyzed with proofs. We also analyze with an example that the optimal scheme is not feasible to be achieved in $\tau$ -constrained stochastic data imputation ( $\tau$ -SDI), but still, our proposed solution identifies an expected-optimal scheme in $\tau$ -SDI. Extensive experiments on four data collections show that TRIP retrieves on average 20 percent missing values and achieves the same high recall that was reached by the retrieving-based approach.

Peter Triantafillou - One of the best experts on this subject based on the ideXlab platform.

  • Pyracanthus: A scalable solution for DHT-independent content-based publish/subscribe data networks
    Information Systems, 2011
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    We study the problems associated with building large-scale, content-based, publish/subscribe networks. In particular, we focus on network-independent solutions, in an effort to isolate and bypass the difficult problems of ensuring the desirable underlying-network properties of scalability, fault tolerance, high performance, and adaptability to user and network dynamics. For this reason, we assume a popular overlay network infrastructure, based on Distributed Hash Tables, over which our pub/sub system will be built. We present Pyracanthus which embodies and can be configured using a suite of novel alternative components, which are categorized according to their ability to handle numerical and/or String Attribute predicates and according to whether they are stateful/stateless. We present in detail each component consisting of algorithms for in-network indexing and storing of numerical and/or String-Attribute subscription predicates, algorithms for matching events to relevant subscriptions, and any additional state. We analytically and experimentally analyze the performance of the alternative algorithms, exposing and quantifying related trade-offs.

  • internet scale String Attribute publish subscribe data networks
    Conference on Information and Knowledge Management, 2005
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over String-Attributes involving prefix, suffix, containment, and equality operators in large-scale data networks. Our first design decision is to employ distributed hash tables (DHTs) for the data network's topology, harnessing their desirable properties. Our next design decision is to derive DHT-independent solutions, treating DHT as a black box. Second, we exploit this infrastructure to develop efficient content based publish/subscribe systems. The main contribution here are algorithms for the efficient processing of queries (subscriptions) and events (publications). Specifically, we show that our subscription processing algorithms require O(logN) messages for a N-node network, and our event processing algorithms require O(l x logN) messages (with l being the average String length).Third, we develop algorithms for optimizing the processing of multi-dimensional events, involving several String Attributes. Further to our analysis, we provide simulation-based experiments showing promising performance results in terms of number of messages, required bandwidth, load balancing, and response times.

  • CIKM - Internet scale String Attribute publish/subscribe data networks
    Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05, 2005
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over String-Attributes involving prefix, suffix, containment, and equality operators in large-scale data networks. Our first design decision is to employ distributed hash tables (DHTs) for the data network's topology, harnessing their desirable properties. Our next design decision is to derive DHT-independent solutions, treating DHT as a black box. Second, we exploit this infrastructure to develop efficient content based publish/subscribe systems. The main contribution here are algorithms for the efficient processing of queries (subscriptions) and events (publications). Specifically, we show that our subscription processing algorithms require O(logN) messages for a N-node network, and our event processing algorithms require O(l x logN) messages (with l being the average String length).Third, we develop algorithms for optimizing the processing of multi-dimensional events, involving several String Attributes. Further to our analysis, we provide simulation-based experiments showing promising performance results in terms of number of messages, required bandwidth, load balancing, and response times.

Ioannis Aekaterinidis - One of the best experts on this subject based on the ideXlab platform.

  • Pyracanthus: A scalable solution for DHT-independent content-based publish/subscribe data networks
    Information Systems, 2011
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    We study the problems associated with building large-scale, content-based, publish/subscribe networks. In particular, we focus on network-independent solutions, in an effort to isolate and bypass the difficult problems of ensuring the desirable underlying-network properties of scalability, fault tolerance, high performance, and adaptability to user and network dynamics. For this reason, we assume a popular overlay network infrastructure, based on Distributed Hash Tables, over which our pub/sub system will be built. We present Pyracanthus which embodies and can be configured using a suite of novel alternative components, which are categorized according to their ability to handle numerical and/or String Attribute predicates and according to whether they are stateful/stateless. We present in detail each component consisting of algorithms for in-network indexing and storing of numerical and/or String-Attribute subscription predicates, algorithms for matching events to relevant subscriptions, and any additional state. We analytically and experimentally analyze the performance of the alternative algorithms, exposing and quantifying related trade-offs.

  • internet scale String Attribute publish subscribe data networks
    Conference on Information and Knowledge Management, 2005
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over String-Attributes involving prefix, suffix, containment, and equality operators in large-scale data networks. Our first design decision is to employ distributed hash tables (DHTs) for the data network's topology, harnessing their desirable properties. Our next design decision is to derive DHT-independent solutions, treating DHT as a black box. Second, we exploit this infrastructure to develop efficient content based publish/subscribe systems. The main contribution here are algorithms for the efficient processing of queries (subscriptions) and events (publications). Specifically, we show that our subscription processing algorithms require O(logN) messages for a N-node network, and our event processing algorithms require O(l x logN) messages (with l being the average String length).Third, we develop algorithms for optimizing the processing of multi-dimensional events, involving several String Attributes. Further to our analysis, we provide simulation-based experiments showing promising performance results in terms of number of messages, required bandwidth, load balancing, and response times.

  • CIKM - Internet scale String Attribute publish/subscribe data networks
    Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05, 2005
    Co-Authors: Ioannis Aekaterinidis, Peter Triantafillou
    Abstract:

    With this work we aim to make a three-fold contribution. We first address the issue of supporting efficiently queries over String-Attributes involving prefix, suffix, containment, and equality operators in large-scale data networks. Our first design decision is to employ distributed hash tables (DHTs) for the data network's topology, harnessing their desirable properties. Our next design decision is to derive DHT-independent solutions, treating DHT as a black box. Second, we exploit this infrastructure to develop efficient content based publish/subscribe systems. The main contribution here are algorithms for the efficient processing of queries (subscriptions) and events (publications). Specifically, we show that our subscription processing algorithms require O(logN) messages for a N-node network, and our event processing algorithms require O(l x logN) messages (with l being the average String length).Third, we develop algorithms for optimizing the processing of multi-dimensional events, involving several String Attributes. Further to our analysis, we provide simulation-based experiments showing promising performance results in terms of number of messages, required bandwidth, load balancing, and response times.

Shuangli Shan - One of the best experts on this subject based on the ideXlab platform.

  • webput a web aided data imputation system for the general type of missing String Attribute values
    International Conference on Data Engineering, 2019
    Co-Authors: Shuangli Shan, Qiang Yang, Jia Zhu, Mohamed A Sharaf, Xiaofang Zhou
    Abstract:

    In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.

  • ICDE - WebPut: A Web-Aided Data Imputation System for the General Type of Missing String Attribute Values
    2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019
    Co-Authors: Shuangli Shan, Qiang Yang, Jia Zhu, Mohamed A Sharaf, Li Yang, Xiaofang Zhou
    Abstract:

    In this demonstration, we present an end-to-end web-aided data imputation prototype system named WebPut. WebPut consults the Web for imputing the missing values in a local database when the traditional inferring-based imputation method has difficulties in getting the right answers. Specifically, WebPut investigates the interaction between the local inferring-based imputation methods and the web-based retrieving methods and shows that retrieving a small number of selected missing values can greatly improve the imputation recall of the inferring-based methods. Besides, WebPut also incorporates a crowd intervention component that can get advice from humans in case that the web-based imputation methods may have difficulties in making the right decisions. We demonstrate, step by step, how WebPut fills an incomplete table with each of its components.

Premkumar Devanbu - One of the best experts on this subject based on the ideXlab platform.

  • Static checking of dynamically generated queries in database applications
    ACM Transactions on Software Engineering and Methodology, 2007
    Co-Authors: Gary Wassermann, Carl Gould, Premkumar Devanbu
    Abstract:

    Many data-intensive applications dynamically construct queries in response to client requests and execute them. Java servlets, for example, can create Strings that represent SQL queries and then send the queries, using JDBC, to a database server for execution. The servlet programmer enjoys static checking via Java's strong type system. However, the Java type system does little to check for possible errors in the dynamically generated SQL query Strings. Thus, a type error in a generated selection query (e.g., comparing a String Attribute with an integer) can result in an SQL runtime exception. Currently, such defects must be rooted out through careful testing, or (worse) might be found by customers at runtime. In this article, we present a sound, static program analysis technique to verify that dynamically generated query Strings do not contain type errors. We describe our analysis technique and provide soundness results for our static analysis algorithm. We also describe the details of a prototype tool based on the algorithm and present several illustrative defects found in senior software-engineering student-team projects, online tutorial examples, and a real-world purchase order system written by one of the authors.

  • ICSE - JDBC checker: a static analysis tool for SQL/JDBC applications
    Proceedings. 26th International Conference on Software Engineering, 1
    Co-Authors: Carl Gould, Premkumar Devanbu
    Abstract:

    In data-intensive applications, it is quite common for the implementation code to dynamically construct database query Strings and execute them. For example, a typical Java servlet Web service constructs SQL query Strings and dispatches them over a JDBC connector to an SQL-compliant database. The servlet programmer enjoys static checking via Java's strong type system. However, the Java type system does little to check for possible errors in the dynamically generated SQL query Strings. For example, a type error in a generated selection query (e.g., comparing a String Attribute with an integer) can result in an SQL runtime exception. Currently, such defects must be rooted out through careful testing, or (worse) might be found by customers at runtime. In this paper, we describe JDBC Checker, a sound static analysis tool to verify the correctness of dynamically generated query Strings. We have successfully applied the tool to find known and unknown defects in realistic programs using JDBC. We give a short description of our tool in this paper.

  • ICSE - Static checking of dynamically generated queries in database applications
    Proceedings. 26th International Conference on Software Engineering, 1
    Co-Authors: Carl Gould, Premkumar Devanbu
    Abstract:

    Many data-intensive applications dynamically constructqueries in response to client requests and execute them.Java servlets, e.g., can create String representations ofSQL queries and then send the queries, using JDBC, to adatabase server for execution. The servlet programmer enjoysstatic checking via Javaýs strong type system. However,the Java type system does little to check for possible errorsin the dynamically generated SQL query Strings. Thus,a type error in a generated selection query (e.g., comparinga String Attribute with an integer) can result in an SQLruntime exception. Currently, such defects must be rootedout through careful testing, or (worse) might be found bycustomers at runtime. In this paper, we present a sound,static, program analysis technique to verify the correctnessof dynamically generated query Strings. We describe ouranalysis technique and provide soundness results for ourstatic analysis algorithm. We also describe the details of aprototype tool based on the algorithm and present severalillustrative defects found in senior software-engineeringstudent-team projects, online tutorial examples, and a real-worldpurchase order system written by one of the authors.