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apache
tika
Java2016–2017
apache / tika

tika

The Apache Tika toolkit detects and extracts metadata and text from over a thousand different file types (such as PPT, XLS, and PDF).

3Distinct people
3Mentions
0Explicit recommenders
4.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

The Apache Tika toolkit detects and extracts metadata and text from over a thousand different file types (such as PPT, XLS, and PDF).

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month3 dated mentions

Observed mentions: 2016-06-16 20:13:11 UTC to 2017-04-07 09:02:28 UTC.

0122016-06-01 00:00:00 UTC to 2016-07-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsJun 20162016-07-01 00:00:00 UTC to 2016-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-08-01 00:00:00 UTC to 2016-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-09-01 00:00:00 UTC to 2016-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-10-01 00:00:00 UTC to 2016-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-11-01 00:00:00 UTC to 2016-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsNov 20162016-12-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2017-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-02-01 00:00:00 UTC to 2017-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-03-01 00:00:00 UTC to 2017-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-04-01 00:00:00 UTC to 2017-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsApr 2017

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jun 20162016-06-01 00:00:00 UTC2016-07-01 00:00:00 UTC202
Jul 20162016-07-01 00:00:00 UTC2016-08-01 00:00:00 UTC000
Aug 20162016-08-01 00:00:00 UTC2016-09-01 00:00:00 UTC000
Sep 20162016-09-01 00:00:00 UTC2016-10-01 00:00:00 UTC000
Oct 20162016-10-01 00:00:00 UTC2016-11-01 00:00:00 UTC000
Nov 20162016-11-01 00:00:00 UTC2016-12-01 00:00:00 UTC000
Dec 20162016-12-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
Jan 20172017-01-01 00:00:00 UTC2017-02-01 00:00:00 UTC000
Feb 20172017-02-01 00:00:00 UTC2017-03-01 00:00:00 UTC000
Mar 20172017-03-01 00:00:00 UTC2017-04-01 00:00:00 UTC000
Apr 20172017-04-01 00:00:00 UTC2017-05-01 00:00:00 UTC101

What Hacker News says

3 sources
We are adding this now to our tensor library: https://github.com/deeplearning4j/nd4j/pull/1750 I've also added numpy interop via our new python interface jumpy: https://github.com/deeplearning4j/jumpy We are doing a lot more than autograd though, this is going to support dynamic computation graphs, give you direct access to a graph data structure and will later be usable from nd4s (our scala wrapper) Rather than spending time going back and forth implementing all of those things you could just pitch in with our existing efforts (hint: you'd actually be getting something done rather than debating ;)) We have a parameter server for word2vec, various kinds of optimizers and the like:https://github.com/deeplearning4j/nd4j/tree/master/nd4j-para... I'd also just like to note for anyone else reading this: Mulling over doing something helps no on
Read the rest
e. If you see something that's open source that's close to what you want try engaging the authors to see what they have to say. Maybe they will guide you. We've done that recently for our lapack integration with cpu and gpu as well as various neural net implementations. No offense but it kills me to see comments like this. I see tons of people complaining about features yet doing nothing to add them let alone engaging open source authors. It's kinda funny - every time someone has actually did that I've hired them. The developers that actually take action when engaging open source are amazing people.I have a feeling it's because they take the time to learn and get their feet wet even if it's initimidating. Other neat community initiatives include flink: https://issues.apache.org/jira/browse/FLINK-5782 Nasa (Apache Tika): https://github.com/apache/tika/pull/165 A language for our ETL library DataVec (supports binary vectorization AND sql like transformations!): https://github.com/deeplearning4j/DataVec/issues/224 A scala lib like tensorflow built on top of nd4j: https://github.com/ThoughtWorksInc/DeepLearning.scala Our spark ml integration: https://github.com/deeplearning4j/deeplearning4j/tree/master... The community is very active. We have 4200 people in a gitter room alone: http://gitter.im/deeplearning4j/deeplearning4j
In Some Lesser Known Machine Learning Libraries
Apache Tika is a text extraction toolkit. They store a wide selection of file types for their parser tests: https://github.com/apache/tika/tree/master/tika-parsers/src/... For large sets of some common media types take a look at the govdocs1 corpus: http://digitalcorpora.org/corp/files/govdocs1/by_type/ For an odd example, sometimes a google search will turn something up.: https://www.google.com/?q=filetype:xlsx
In Ask HN: Is there a site providing example files for “all” media types?

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