HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM

Kazuki Kawamura, Akihiro Yamamoto
9/28/2024
cs.IRcs.LG

No confident code implementation found for this paper.

Abstract

In this paper, we propose a novel method for extracting information from HTML tables with similar contents but with a different structure. We aim to integrate multiple HTML tables into a single table for retrieval of information containing in various Web pages. The method is designed by extending tree-structured LSTM, the neural network for tree-structured data, in order to extract information that is both linguistic and structural information of HTML data. We evaluate the proposed method through experiments using real data published on the WWW.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Cite this paper

@article{kawamura2024htmllstm,
  title  = {HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM},
  author = {Kazuki Kawamura and Akihiro Yamamoto},
  year   = {2024},
  eprint = {2409.19445},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.19445v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2409.19445.svg)](https://codeofpaper.com/paper/2409.19445)

Discussion