Yair Censor and Stavros A. Zenios, Oxford University Press, New York, 1997, 539 pp., ISBN 0-19-510062-X, $85.00

Parallel Optimization: Theory, Algorithms and Applications

Process modeling allows for analysis and improvement of processes that coordinate multiple people and tools working together to carry out a task. Process modeling typically focuses on the normative process, that is, how the collaboration transpires when everything goes as desired. Unfortunately, real-world processes rarely proceed that smoothly. A more complete analysis of a process requires that the process model also include details about what to do when exceptional situations arise. We have found that, in many cases, there are abstract patterns that capture the relationship between exception handling tasks and the normative process. Just as object-oriented design patterns facilitate the development, documentation, and maintenance of object-oriented programs, we believe that process patterns can facilitate the development, documentation, and maintenance of process models. In this paper, we focus on the exception handling patterns that we have observed over many years of process modeling. We describe these patterns using three process modeling notations: UML 2.0 Activity Diagrams, BPMN, and Little-JIL. We present both the abstract structure of the pattern as well as examples of the pattern in use. We also provide some preliminary statistical survey data to support the claim that these patterns are found commonly in actual use and discuss the relative merits of the three notations with respect to their ability to represent these patterns.

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Exception Handling Patterns for Process Modeling

The automatic consolidation of database records from many heterogeneous sources into a single repository requires solving several information integration tasks. Although tasks such as coreference, schema matching, and canonicalization are closely related, they are most commonly studied in isolation. Systems that do tackle multiple integration problems traditionally solve each independently, allowing errors to propagate from one task to another. In this paper, we describe a discriminatively-trained model that reasons about schema matching, coreference, and canonicalization jointly. We evaluate our model on a real-world data set of people and demonstrate that simultaneously solving these tasks reduces errors over a cascaded or isolated approach. Our experiments show that a joint model is able to improve substantially over systems that either solve each task in isolation or with the conventional cascade. We demonstrate nearly a 50% error reduction for coreference and a 40% error reduction for schema matching.

/pdf/a-unified-approach-for-schema-matching-coreference-and-2qq7muq538.pdf

A unified approach for schema matching, coreference and canonicalization

Recently, many advanced machine learning approaches have been proposed for coreference resolution; however, all of the discriminatively-trained models reason over mentions rather than entities. That is, they do not explicitly contain variables indicating the “canonical” values for each attribute of an entity (e.g., name, venue, title, etc.). This canonicalization step is typically implemented as a post-processing routine to coreference resolution prior to adding the extracted entity to a database. In this paper, we propose a discriminatively-trained model that jointly performs coreference resolution and canonicalization, enabling features over hypothesized entities. We validate our approach on two different coreference problems: newswire anaphora resolution and research paper citation matching, demonstrating improvements in both tasks and achieving an error reduction of up to 62% when compared to a method that reasons about mentions only.

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An Entity Based Model for Coreference Resolution

The wide-spread use of mobile devices has made it possible to develop mobile voting system as a complement to the existing electronic voting system. However, due to limited onboard resource, it is challenging to achieve both efficiency and security strength for mobile voting system. Conventional solution is to either use symmetric encryption algorithms or hybrid symmetric and asymmetric algorithms at the expense of weaker security strength. In our proposed mobile voting scheme, the users’ votes are secured by using the elliptic curve cryptography (ECC) algorithm. ECC is chosen as it has smaller key size than other public key cryptographies; and its homomorphic encryption property which is able to keep users’ anonymity. We evaluate the method of ECDH with AES and ECC in comparison with our proposed method. The experiment demonstrates that our proposed ECC based scheme can outperform the traditional hybrid symmetric and asymmetric cryptographic scheme in the context of mobile evoting environment.

An Efficient Mobile Voting System Security Scheme Based on Elliptic Curve Cryptography

It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can be constructed by automatically extracting titles, authors, and conference information from online papers. A common difficulty in consolidating data from multiple sources is that records are referenced in a variety of ways (e.g. abbreviations, aliases, and misspellings). Therefore, it can be difficult to construct a single, standard representation to present to the user. We refer to the task of constructing this representation as canonicalization. Despite its importance, there is little existing work on canonicalization.In this paper, we explore the use of edit distance measures to construct a canonical representation that is "central" in the sense that it is most similar to each of the disparate records. This approach reduces the impact of noisy records on the canonical representation. Furthermore, because the user may prefer different styles of canonicalization, we show how different edit distance costs can result in different forms of canonicalization. For example, reducing the cost of character deletions can result in representations that favor abbreviated forms over expanded forms (e.g. KDD versus Conference on Knowledge Discovery and Data Mining). We describe how to learn these costs from a small amount of manually annotated data using stochastic hill-climbing. Additionally, we investigate feature-based methods to learn ranking preferences over canonicalizations. These approaches can incorporate arbitrary textual evidence to select a canonical record. We evaluate our approach on a real-world publications database and show that our learning method results in a canonicalization solution that is robust to errors and easily customizable to user preferences.

/pdf/canonicalization-of-database-records-using-adaptive-20fbfp1sqy.pdf

Canonicalization of database records using adaptive similarity measures

In this paper we outline an approach for modeling election processes and then performing rigorous analysis to verify that these process models meet selected behavioral requirements. We briey outline some high-level requirements that an election process must satisfy and demonstrate how these are refined into a collection of lower-level properties that can be used as the basis for verification. We present a motivating example of an election process modeled using the Little-JIL process definition language, capture the lower-level properties using the PROPEL property elicitation tool, and perform formal analysis to verify that the process model adheres to these properties using the FLAVERS finite-state verifier. We illustrate how this approach can identify errors in the process model when a property is violated.

/pdf/specifying-and-verifying-requirements-for-election-processes-3id75et1qq.pdf

Specifying and verifying requirements for election processes

This demonstration shows a prototype tool that projects an impression of how execution of a formally defined process will facilitate dispute resolution. Tool flexibility supports projecting the look and feel of a range of different processes, facilitating user evaluation of alternatives.

/pdf/a-process-driven-tool-to-support-online-dispute-resolution-anf8umw9t6.pdf

A process-driven tool to support online dispute resolution

This poster is showing that process definitions can be effective in specifying and guiding Online Dispute Resolution (ODR) to facilitate effective interactions and mediation among disputants. Simply specifying these interactions is not sufficient to assure that the mediator and the participants are effectively engaged in performing their roles in such processes. Our project is developing a system to translate process definition specifications into actions that are reflected in the screens that participants and mediators view while participating in these processes. Thus we are demonstrating that, with the help of the system we are building, the process definition can control changes to the user interfaces of the participants involved in the process itself. This should enable the process to keep all users continually informed about the state of the process in which they are participating including the actions that the user needs to perform. This should improve the ability of the process to be an effective aid to ODR mediation.

http://laser.cs.umass.edu/techreports/07-11.pdf

Matthew Marzilli

Papers

Canonicalization of database records using adaptive similarity measures

Specifying and verifying requirements for election processes

A process-driven tool to support online dispute resolution

Using process definitions to drive user interactions with digital government systems