A Lightweight Approach to Extract Interschema Properties from Structured, Semi-Structured and Unstructured Sources in a Big Data Scenario

被引：5

作者：

Cauteruccio, Francesco ^{[1
]}

Lo Giudice, Paolo ^{[2
]}

Musarella, Lorenzo ^{[2
]}

Terracina, Giorgio ^{[1
]}

Ursino, Domenico ^{[3
]}

Virgili, Luca ^{[3
]}

机构：

[1] Univ Calabria, Dipartimento Matemat & Informat, I-87036 Arcavacata Di Rende, CS, Italy

[2] Univ Mediterranea Reggio Calabria, Dipartimento Ingn Informaz Infrastrutture & Energ, Via Univ,25 Gia Salita Melissari, I-89124 Reggio Di Calabria, CF, Italy

[3] Univ Politecn Marche, Dipartimento Ingn Informaz, Via Brecce Bianche 12, I-60131 Ancona, Italy

来源：

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING | 2020年 / 19卷 / 03期

关键词：

Unstructured sources; interschema property derivation; structuring unstructured data; big data; METADATA QUALITY; DIGITAL REPOSITORIES; SIMILARITY; CLASSIFICATION; CONSTRUCTION; INTEGRATION; SYSTEM; MODEL; DIKE;

D O I：

10.1142/S0219622020500182

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The knowledge of interschema properties (e.g., synonymies, homonymies, hyponymies and subschema similarities) plays a key role for allowing decision-making in sources characterized by disparate formats. In the past, wide amount and variety of approaches to derive interschema properties from structured and semi-structured data have been proposed. However, currently, it is esteemed that more than 80% of data sources are unstructured. Furthermore, the number of sources generally involved in an interaction is much higher than in the past. As a consequence, the necessity arises of new approaches to address the interschema property derivation issue in this new scenario. In this paper, we aim at providing a contribution in this setting by proposing an approach capable of uniformly extracting interschema properties from a huge number of structured, semi-structured and unstructured sources.

引用

页码：849 / 889

页数：41

共 50 条

[41] Information discovery from semi-structured sources - Application to astronomical literature
Dkaki, T
Dousset, B
Egret, D
Mothe, J
COMPUTER PHYSICS COMMUNICATIONS, 2000, 127 (2-3) : 198 - 206
[42] Universal data capture technology from semi-structured forms
Tuganbaev, D
Pakhchanian, A
Deryagin, D
EIGHTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS 1 AND 2, PROCEEDINGS, 2005, : 458 - 462
[43] Efficient substructure discovery from large semi-structured data
Asai, T
Abe, K
Kawasoe, S
Sakamoto, H
Arimura, H
Arikawa, S
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2004, E87D (12): : 2754 - 2763
[44] Data extraction from semi-structured web pages by clustering
Vuong, Le Phong Bao
Gao, Xiaoying
Zhang, Mengjie
2006 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE, (WI 2006 MAIN CONFERENCE PROCEEDINGS), 2006, : 374 - +
[45] Efficient substructure discovery from large semi-structured data
Asai, T
Abe, K
Kawaoe, S
Arimura, H
Sakamoto, H
Arikawa, S
PROCEEDINGS OF THE SECOND SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 2002, : 158 - 174
[46] Discovering frequent substructures from hierarchical semi-structured data
Cong, G
Yi, L
Liu, B
Wang, K
PROCEEDINGS OF THE SECOND SIAM INTERNATIONAL CONFERENCE ON DATA MINING, 2002, : 175 - +
[47] Knowledge discovery from semi-structured data for conceptual organization
Gupta, S.
Goyal, R.
Shubham, K.
Dey, L.
Malik, A.
Chaudhury, S.
Bhattacharya, S.
2006 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY, WORKSHOPS PROCEEDINGS, 2006, : 291 - +
[48] Extraction and transformation of data from semi-structured text files using a declarative approach
Raminhos, R.
Moura-Pires, J.
ICEIS 2007: PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS: DATABASES AND INFORMATION SYSTEMS INTEGRATION, 2007, : 199 - +
[49] An Overview on XML Semantic Disambiguation from Unstructured Text to Semi-Structured Data: Background, Applications, and Ongoing Challenges
Tekli, Joe
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2016, 28 (06) : 1383 - 1407
[50] Comparing avian species richness estimates from structured and semi-structured citizen science data
Fang-Yu Shen
Tzung-Su Ding
Jo-Szu Tsai
Scientific Reports, 13

← 1 2 3 4 5 →