Integration of Data Warehouse and Unstructured Business Documents

Alqarni, Ahmed Abdullah; Pardede, Eric

doi:10.1109/nbis.2012.59

Cited by 8 publications

(9 citation statements)

References 24 publications

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“…(Alqarni & Pardede, 2012) show the integration of DWs and unstructured business documents. They propose a multi-layer schema for mapping structured data stored in a data warehouse and unstructured data in business-related documents (invoices, contracts and catalogs).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Peral

Ferrández

Gregorio

et al. 2015

Ecological Informatics

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Section: Accepted Manuscriptmentioning

confidence: 99%

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Peral

Ferrández

Gregorio

et al. 2015

Ecological Informatics

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“…Using WordNet to find semantic similarity for two XML Schemas element names are described in detail in [13]. The most common measures are Lin and Wu and Palmer's measures [2,13].…”

Section: B) Language-based Matchersmentioning

confidence: 99%

“…Using WordNet to find semantic similarity for two XML Schemas element names are described in detail in [13]. The most common measures are Lin and Wu and Palmer's measures [2,13]. Lin's measures information context by finding the Lowest Common Subsumer (LCS) of two concepts with the sum of the Information Content (IC) of these concepts.…”

Section: B) Language-based Matchersmentioning

confidence: 99%

Internal Filtering Approach toward Efficiency Optimization of Matching Large Scale XML Schemas

Alqarni

Pardede

2013

2013 16th International Conference on Network-Based Information Systems

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XML Schema matching plays a significant role in the integration of different XML Schemas by finding similar corresponding elements. XML Schema elements' properties and their relation to surrounding elements play significant role in improving the quality of matching process. Investigating all measures for each element in two schemas can result in a long execution time, which reduces the performance of the matching process. The feasibility of performance is becoming significant in particular in large scale XML Schema with all that features and surroundings. Since internal features of an element represents between 40-60% of the total similarity value, it should be utilised to filter elements that yield lower internal similarity value based on a predefined threshold. Thus, we propose to use element's internal features as a filter to exclude any element that is lower to certain predefined threshold. We also present an optimum threshold that can be used in the filtering approach. The idea is to detect using the internal features the elements that are highly likely to be dissimilar and excluded them from the next phase of element's context (element's surroundings) investigations. The outcome of imposing this approach is promising not only for improving the matching efficiency per see, but also for maintaining an acceptable quality results that are very close to non-filter approach.

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“…Most business organizations store unstructured data in document format. These documents are essential in the decision-making process [1].…”

Section: Introductionmentioning

confidence: 99%

“…[3] extracts schema from unstructured data using Hadoop Distributed File System (HDFS). We notice from their work, that HDFS has the following limitations: (1). HDFS running on a server, not on the cloud, (2).…”

Section: Introductionmentioning

confidence: 99%

a Schema Extraction of Document-Oriented Database for Data Warehouse

Istiqamah

Wiharja

2021

ijoict

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The data warehouse is a very famous solution for analyzing business data from heterogeneous sources. Unfortunately, a data warehouse only can analyze structured data. Whereas, nowadays, thanks to the popularity of social media and the ease of creating data on the web, we are experiencing a flood of unstructured data. Therefore, we need an approach that can "structure" the unstructured data into structured data that can be processed by the data warehouse. To do this, we propose a schema extraction approach using Google Cloud Platform that will create a schema from unstructured data. Based on our experiment, our approach successfully produces a schema from unstructured data. To the best of our knowledge, we are the first in using Google Cloud Platform for extracting a schema. We also prove that our approach helps the database developer to understand the unstructured data better.

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Integration of Data Warehouse and Unstructured Business Documents

Cited by 8 publications

References 24 publications

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Enrichment of the phenotypic and genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Internal Filtering Approach toward Efficiency Optimization of Matching Large Scale XML Schemas

a Schema Extraction of Document-Oriented Database for Data Warehouse

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