Algebraic Signatures for Scalable Web Data Integration for Electronic Commerce Transactions
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Bibliographic record
Abstract
ABSTRACT E-commerce transactions involve the access of data from enterprise-wide information. Providing enterprise-wide information is becoming increasingly difficult because of problems inherent in identifying semantic equivalent data. Web data integration consolidates and standardizes Web data, thus making Web data readily available to meet e-commerce needs. Integrating data from different sources involves combining concepts and knowledge of such data into a global view, so users can access such data without relying on the complex organizational structures of the underlying data sources. Unfortunately, most existing efforts involve significant manual input and adopt ad hoc approaches to data integration, ignoring the theoretical foundations of, and the necessary formalisms to specify, the integration process. In this paper, we leverage algebraic signatures to specify components of the integration system. We present an algebraic data that reduces the topological structure of Web data sources to regular expressions. We define algebraic operators and functions to manipulate objects in the algebraic model. Central to the integration process is a filter mechanism that recognizes a regulated schema so that all the participating schemas are guaranteed to be in the same format. We also show that our approach guarantees a scalable and correct integration system. Keywords: Web data integration, E-Commerce, Algebraic Signatures, Semistructured Data Model (ProQuest Information and Learning: ... denotes formulae omitted.) 1. Introduction The Internet offers a virtual marketplace where buyers and sellers exchange goods and services. E-commerce involves business activities that deal with the exchange of values for goods and services on the Internet where all transactions are driven electronically. E-commerce, by nature, is a self-service model that allows the customer to locate a merchant's Web site, get product information, initiate product order and make payments. Locating products or businesses on the Web is an important integral aspect of e-commerce transactions. Therefore, participants have to contend with information overload on the Web, as it is the responsibility of the users to locate and interpret Web data. Regardless of the increasing volumes of e-commerce sites, e-commerce transactions come with some challenges. Maamar (2003) identifies the following challenges that affect e-commerce operations: 1) The user has to identify the relevant Web sites to access catalogs; 2) It is necessary for the user to understand how the Web sites operate; 3) The user has to specify his / her needs according to the characteristics or terminology of the Web sites; and 4) there is also security concerns in dealing with sensitive information, such as user's account information. The issue of secure e-commerce infrastructure has been extensively addressed in the literature [Bryant and Colledge, 2002; Evincible, 2003; Tygar, 1996; VeriSign, 2003]. However, data infrastructure (identifying, interpreting and standard format) for e-commerce data on the Web is largely ignored. Web users, and in particular, e-commerce actors desire an environment where data is transparent (but appears visible) to all the participants. Therefore, a that makes e-commerce data on the Web visible to all the actors is desirable. Web data integration provides a framework to consolidate and standardize Web data, thus making Web data readily available. We present a scalable integration system that is capable of integrating Web data sources. Our design philosophy hinges on three pivotal components - suitable input, appropriate integration methodology and transparent integration output. We believe that applying appropriate integration methodology based on sound theoretical foundation to a set of well-formed input schemas will generate the desired integration output that is transparent. The we propose leverages algebraic signatures with sound integration principles and algorithm to guarantee scalability and correctness of the integration system. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it