Evaluation of date extraction tools for Python

Introduction

Although text is ubiquitous on the Web, extracting information from web pages can prove to be difficult, and an important problem remains as to the most efficient way to gather language data. Metadata extraction is part of data mining and knowledge extraction techniques. Dates are critical components since they are relevant both from a philological standpoint and in the context of information technology.

In most cases, immediately accessible data on retrieved webpages do not carry substantial or accurate information: neither the URL nor the server response provide a reliable way to date a web document, i.e. to find when it was written or modified. In that case it is necessary to fully parse the document or apply robust scraping patterns on it.

State of the art

Diverse extraction and scraping techniques are routinely used on web document collections by companies and research institutions alike. Content extraction mostly draws on Document Object Model (DOM) examination, that is on considering a given HTML document as a tree structure whose nodes represent parts of the document to be operated on. Less thorough and not necessarily faster alternatives use superficial search patterns such as regular expressions in order to capture desirable excerpts …

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A module to extract date information from web pages

Description

Metadata extraction

Diverse content extraction and scraping techniques are routinely used on web document collections by companies and research institutions alike. Being able to better qualify the contents allows for insights based on metadata (e.g. content type, authors or categories), better bandwidth control (e.g. by knowing when webpages have been updated), or optimization of indexing (e.g. language-based heuristics, LRU cache, etc.).

In short, metadata extraction is useful for different kinds of purposes ranging from knowledge extraction and business intelligence to classification and refined visualizations. It is often necessary to fully parse the document or apply robust scraping patterns, there are for example webpages for which neither the URL nor the server response provide a reliable way to date the document, that is find when it was written.

Context

I regularly work on improving the extraction methods for the web collections at my home institutions. They are unique as they combine both the quantity resulting from broad web crawling and the quality obtained by carefully extracting text and metadata as well as rejecting documents that do not match certain criteria. In that sense, I already published work on methods to derive metadata from web documents in order …

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