WDEE: Web Data Extraction by Example
Web data extraction systems in use today transform semi-structured Web documents and deliver structured documents to end users. Some systems provide a visual interface to users to generate the extraction rules. However, to end users, the visual effect of Web documents is lost during the transformation process. In this paper, we propose an approach that allows a user to query extracted documents without knowledge of formal query language. We bridge the gap between visual effect of Web documents and structured documents extracted by providing a QBE-like (Query by Example) interface named Wdee. The principle component of our method is the notion of a document schema. Document schemata are patterns of structures embedded in documents. Wdee generates tree skeletons based on schema information and a user may execute queries by input condition in the skeltons. By maintaining the mapping relation among schemata of Web documents and extracted documents, a visual example may be presented to end users. With the example, Wdee allows a user to construct tree skeletons in a manner that resembles the browsing of Web pages.

title: WICCAP: from semi-structured data to structured data
abstract: Web data extraction is a technique for extracting and integrating data from Web based semistructured data. Wrappers function like the kernel of Web data extraction systems providing information mediator between users and a large number of heterogeneous data sources. Typically, they process semistructured documents generated from structured databases based on rules that are usually hidden to users. Much research has been done to use various methods to represent the knowledge of hidden rules and exploit techniques such as grammar induction, inductive logic programming, etc., to discover these rules that can be used by wrappers to extract data. An important property of semistructured data is its hierarchical structure. Intuitively, we can devise a method that can use this structure information to generate wrappers. We describe a Web data extraction system - WICCAP and its internal Web Data Extraction Language (WDEL) that provides unified view of Web data resources and extracted data. We describe some rule generation features of WICCAP and provide detailed description of the internal language and its implementation. We have conducted experiments to show the ease on generating wrappers with this approach.

title: Web data extraction based on structural similarity
abstract: Web data-extraction systems in use today mainly focus on the generation of extraction rules, i.e., wrapper induction. Thus, they appear ad hoc and are difficult to integrate when a holistic view is taken. Each phase in the data-extraction process is disconnected and does not share a common foundation to make the building of a complete system straightforward. In this paper, we demonstrate a holistic approach to Web data extraction. The principal component of our proposal is the notion of a document schema. Document schemata are patterns of structures embedded in documents. Once the document schemata are obtained, the various phases (e.g. training set preparation, wrapper induction and document classification) can be easily integrated. The implication of this is improved efficiency and better control over the extraction procedure. Our experimental results confirmed this. More importantly, because a document can be represented as avector of schema, it can be easily incorporated into existing systems as the fabric for integration.

title: An Efficient Sort-Based DDM Matching Algorithm for HLA Applications with a Large Spatial Environment
abstract: Simulation is a low cost and safe alternative to solve complex problems in various areas. To promote reuse and interoperability of simulation applications and link geographically dispersed simulation components, distributed simulation was introduced. The high level architecture (HLA) is the IEEE standard for distributed simulation. To optimize communication efficiency between simulation components, HLA defines a data distribution management (DDM) service group for filtering out unnecessary data exchange. It relies on the computation of overlap between update and subscription regions, which is called matching. In this paper, we propose an efficient sort-based DDM matching algorithm for HLA applications with a large spatial environment. A theoretical analysis of our algorithm concludes that it should have good storage and computational scalability. The experimental results have verified the theoretical conclusions by showing that our algorithm has much less storage requirement than the original sort-based matching algorithm and generally has the best computational performance when compared with region-based and the original sort-based matching algorithms.

title: Interprocedural Analysis Based on Guarded Array Regions
abstract: Array data flow information plays an important role for successful automatic parallelization of Fortran programs. This chapter proposes a powerful symbolic array data flow summary scheme to support array privatization and loop parallelization for programs with arbitrary control flow graphs and acyclic call graphs. Our approach summarizes array access information interprocedurally, using guarded array regions. The use of guards allows us to use the information in IF conditions to do path-sensitive data flow summary and thereby to handle difficult cases. We also provide a mechanism to overcome the disadvantages of nonclosed union and difference operations. This improves not only the exactness of summaries, but also the efficiency of the summarizing procedure. Our preliminary result on array privatization shows that our summary scheme is fast and powerful.

title: An Object-Oriented Approach Using a Top-Down and Bottom-Up Process for Manipulative Action Recognition
abstract: Different from many gesture-based human-robot interaction applications, which focused on the recognition of the interactional or the pointing gestures, this paper proposes a vision-based method for manipulative gesture recognition aiming to achieve natural, proactive, and non-intrusive interaction between humans and robots. The main contributions of the paper are an object-centered scheme for the segmentation and characterization of hand trajectory information, the use of particle filtering methods for an action primitive spotting, and the tight coupling of bottom-up and top-down processing that realizes a task-driven attention filter for low-level recognition steps. In contrast to purely trajectory based techniques, the presented approach is called object-oriented w.r.t. two different aspects: it is object-centered in terms of trajectory features that are defined relative to an object, and it uses object-specific models for action primitives. The system has a two-layer structure recognizing both the HMM-modeled manipulative primitives and the underlying task characterized by the manipulative primitive sequence. The proposed top-down and bottom-up mechanism between the two layers decreases the image processing load and improves the recognition rate.

title: Parametric analysis for adaptive computation offloading
abstract: Many programs can be invoked under different execution options, input parameters and data files. Such different execution contexts may lead to strikingly different execution instances. The optimal code generation may be sensitive to the execution instances. In this paper, we show how to use parametric program analysis to deal with this issue for the optimization problem of computation offloading.Computation offloading has been shown to be an effective way to improve performance and energy saving on mobile devices. Optimal program partitioning for computation offloading depends on the tradeoff between the computation workload and the communication cost. The computation workload and communication requirement may change with different execution instances. Optimal decisions on program partitioning must be made at run time when sufficient information about workload and communication requirement becomes available.Our cost analysis obtains program computation workload and communication cost expressed as functions of run-time parameters, and our parametric partitioning algorithm finds the optimal program partitioning corresponding to different ranges of run-time parameters. At run time, the transformed program self-schedules its tasks on either the mobile device or the server, based on the optimal program partitioning that corresponds to the current values of run-time parameters. Experimental results on an HP IPAQ handheld device show that different run-time parameters can lead to quite different program partitioning decisions.

title: Efficient interprocedural analysis for program parallelization and restructuring
abstract: An approach to efficient interprocedural analysis for program parallelization and restructuring is presented. Such analysis is needed for parallelizing loops which contain procedure calls. Our approach captures call effect on data dependencies by propagating the precise information of array subscripts from the called procedure. This allows the optimizing compiler to choose an efficient yet precise data dependence test scheme depending on the complexity of array reference patterns. The other existing methods do not provide such flexibility, hence may suffer from either imprecision or inefficiency. The paper also discusses usage of classical summary information in several important transformations for program parallelization. Experimental results are reported.