Kitten: a tool for normalizing HTML and extracting its textual content
The web is composed of a gigantic amount of documents that can be very useful for information extraction systems. Most of them are written in HTML and have to be rendered by an HTML engine in order to display the data they contain on a screen. HTML file thus mix both informational and rendering content. Our goal is to design a tool for informational content extraction. A linear extraction with only a basic filtering of rendering content would not be enough as objects such as lists and tables are linearly coded but need to be read in a non-linear way to be well interpreted. Besides these HTML pages are often incorrectly coded from an HTML point of view and use a segmentation of blocks based on blank space that cannot be transposed in a text filewithout confusing syntactic parsers. For this purpose, we propose the Kitten tool that first normalizes HTML file into unicode XHTML file, then extracts the informational content into a text filewith a special processing for sentences, lists and tables.
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModellingQuestion AnsweringSimilar Papers 제목 키워드 기반
Autoencoder Watchdog Outlier Detection for Classifiers
Neural networks have often been described as black boxes. A generic neural network trained to differentiate between kittens and puppies will classify a picture of a kumquat as a kitten or a puppy. An autoencoder watch do…
Outlier DetectionregressionHipKittens: Fast and Furious AMD Kernels
AMD GPUs offer state-of-the-art compute and memory bandwidth; however, peak performance AMD kernels are written in raw assembly. To address the difficulty of mapping AI algorithms to hardware, recent work proposes C++ em…
HTML-LSTM: Information Extraction from HTML Tables in Web Pages using Tree-Structured LSTM
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 inf…
RetrievalParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels
Inter-GPU communication has become a major bottleneck for modern AI workloads as models scale and improvements in hardware compute throughput outpace improvements in interconnect bandwidth. Existing systems mitigate this…
STAPI: An Automatic Scraper for Extracting Iterative Title-Text Structure from Web Documents
Formal documents often are organized into sections of text, each with a title, and extracting this structure remains an under-explored aspect of natural language processing. This iterative title-text structure is valuabl…
Headline Generation