similar to: Project Proposal in GSoC 2019

On Sun, Mar 03, 2019 at 05:13:09PM +0000, James Aylett wrote: > On 3 Mar 2019, at 17:01, Olly Betts <olly at survex.com> wrote: > > > I suspect what's going on here is that bootstrap will by default > > download, build and install (into a subdirectory of the build tree) any > > of the autotools for which suitable versions aren't already installed. > >

Hi, I am new to Icecast open source project and I would like to contribute into this open source project. Looking for some kind of guidelines how to get started and where to browse for the open issues or features to look into. Any kind of help would be much appreciated. - Sourav Saha -------------- next part -------------- An HTML attachment was scrubbed... URL:

Thanks for your patience. I'm still confused of what I should do next. If it's not worth changing anything here as it's a rare case, sorry for my PR to github before the reply, maybe you need to close it on github. For another case, should I optimize current code with replacing set to a static array? Or rollback current modification to cjk-tokenizer and try to do some work with the

Thanks Philipp. I agree with you, this looks like some buffer overrun issue. I know I'm using a very old version of icecast software but still I am asking is there any kind of workaround to this problem apart from upgrading the icecast version (which is the last option). Running Valgrind may help to capture the root cause, any thoughts? BTW what's the latest stable version of icecast?

Hi, I am using icecast 2.3.2 and I'm not in position to upgrade the version right away since this version is already in use. Please let me know if you need any additional details for this issue. Nevertheless if there is any potential fix has gone towards this part of code in later versions, I can just use that patch in my current code base. Also I'll try to catch up on Freenode but

Dear mentors and friends working on Xapian: Sorry for bothering you here, please excuse my rudeness. In order to clearly represent my thoughts, I think my words going a bit verbose, thus it is unsuitable to put them in the chat room or it would be a hell for the readers. This email consists of 3 parts, my self introduction (I'm new here) and two question I met while building Xapian from git.

Excuse me, I have met some problem while writing test cases for api_termgen. I added a case for mixed CJK numbers to test_simple, as the example mentioned in #699: > { "", "2千3百", "2[1] 千[2] 3[3] 百[4]"} But it unexpectedly failed. Below are the input and output. I run test with command: > ./runtest ./apitest termgen1 And the test case output is: > Running

Hi All, I'm facing a problem in icecast relay machines. I'm seeing frequently that some of the relay machines are crashing and generates core dump but the reason for the crash is not clear from the trace of the core. Here is how the gdb trace looks like: (gdb) bt #0 0xffffe435 in __kernel_vsyscall () #1 0xf742c607 in raise () from /lib/i386-linux-gnu/libc.so.6 #2 0xf742fa33 in

Hi All, I'm facing a problem in icecast relay machines. I'm seeing frequently that some of the relay machines are crashing and generates core dump but the reason for the crash is not clear from the trace of the core. Here is how the gdb trace looks like: (gdb) bt #0 0xffffe435 in __kernel_vsyscall () #1 0xf742c607 in raise () from /lib/i386-linux-gnu/libc.so.6 #2 0xf742fa33 in

Hello, I wanted to decide the dataset that should be used for Letor stabilisation project. I think 2009 INEX Wikipedia Collection <http://www.mpi-inf.mpg.de/departments/databases-and-information-systems/software/inex/> should work fine. It's a collection of 2,666,190 XML articles, 115 topics <http://inex.mmci.uni-saarland.de/protected/adhoc/2009-topics.zip>, 50,275 qrel

For unsupervised approaches like BM25 this approach works well but letor does not need special weighting for title in this form as it itself assigns weights to title features separately. But I see your concern it would be a problem when BM25 is used on the index with this setup. Hence its preferable to take a note of this uplift in title weight for xapian-letor and normalize it everywhere

Hello, I'm Ayush from New Delhi, India. I am interested in Letor Stabilisation project for GSoC. I have a good background in machine learning. Sorry for getting in so late, university exams were holding me back. I'll try to cover as much as I can in the coming week. I am following the plan of attack suggested on the project page. Following are the things that I have completed: 1.

I am working on "#699 Better tokenisation of mixed CJK numbers", and have implemented a partial patch of Chinese for this ticket. Current code works well with special test cases and all tests in xapian-core could still pass. But I'm confused with exact requirements of the question, for how much we could pay with performance on enabling more cases, and if there are better methods to

Hi, Before starting my proposal, I wanted to know what is the expected output of Letor module. Is it for transfer learning (i.e you learn from one dataset and leverage it to predict the rankings of other dataset) or is it for supervised learning? For instance - Xapian currently powers the Gmane search which is by default based on BM25 weighting scheme and now suppose we want to use LETOR to rank

Hi Olly, Wouldn't setting the weight of terms in title back to normal (e.g. 5 to 1) by below line, automatically adjust the wdfs and field lengths? indexer.index_text(title, 5, "S"); -> indexer.index_text(title, 1, "S"); if it does not then we should include that part in the patch too. I like to create a patch for xapian-letor for resolving common code of xapian.

Hi Parth, I implemented DFR algorithms in Xapian as a part of GSOC last year under the mentorship of Olly. This year, I want to work on analyzing and optimizing the performance of the DFR algorithms and comparing them with BM25.I also want to work on profiling the query expansion schemes and test the relevance(precision and recall) / speed(time taken) of the

Hello James, Parth, Following our discussion on IRC and on code review, the way FeatureVector class works needs some discussion. Presently, the FeatureVector class is defined as follows, with a fixed number of feature count (19): class FeatureVector::Internal : public Xapian::Internal::intrusive_base{ friend class FeatureVector; double label; double score;

Hello, I want to discuss my idea on ranking in IR system which I think can be good extension to Xapian. If I am not too late to discuss it then please consider it. I first give you brief background of me, I am a Masters student working on my thesis in the Information Retrieval. I today only got a mail from one of the professor from Europe whom i am going to join for Ph.D about GSoC and more

Hello, I would like to work with Orange as part of GSoC 2012(and continue henceforth). Apologies for joining in a bit late- i was waiting to get a proper grasp of things before discussing it here. Currently I am a Masters students in Mathematics with my bachelors in Computer Science[integrated dual degree]. Over the last year and a half, I have worked on a few ML projects and have a couple of

Hello All, This time we are working on a weighting scheme "Learning to Rank" which involves machine learning and its a supervised ranking scheme unlike unsupervised schemes like BM25 under GSoC project. This mail intends to discuss the framework of the Learning to Rank in Xapian as a whole. I have thought of the following framework, pour in your insights or issues for the same. This is