Py_ape: Text Data Acquiring, Extracting, Cleaning and Schema Matching in Python

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10246988" target="_blank" >RIV/61989100:27240/20:10246988 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007%2F978-981-33-4370-2_6" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-981-33-4370-2_6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-33-4370-2_6" target="_blank" >10.1007/978-981-33-4370-2_6</a>

Result language

angličtina

Original language name

Py_ape: Text Data Acquiring, Extracting, Cleaning and Schema Matching in Python

Original language description

Py_ape is a package in Python that integrates a number of string and text processing algorithms for collecting, extracting, and cleaning text data from websites, creating frames for text corpora, and matching entities, matching two schemas, mapping and merging two schemas. The functions of Py_ape help the user step-by-step perform data integration and data preparation, based on some popular Python libraries. Especially in the entity matching function of the schema matching and merging phase, we used the Hamming distance algorithm to identify similar string pairs, and the longest common substring similarity algorithm to map data between the columns of schemas. These algorithms help to increase the accuracy of the schema matching process. In addition, in the article, we present experimental results using Py_ape to scrape, clean, match, and merge two sets of data related to aviation crashes, taken from different sources of Kaggle and Wikipedia. The result of the experiment will be evaluated in detail in the rest of the paper. (C) 2020, Springer Nature Singapore Pte Ltd.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Communications in Computer and Information Science. Volume 1306

ISBN

978-981-334-369-6

ISSN

1865-0929

e-ISSN

1865-0937

Number of pages

12

Pages from-to

78-89

Publisher name

Springer

Place of publication

Singapur

Event location

Quy Nhon

Event date

Nov 25, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—