similar to: Letor: Post Mid-Term plan

Hi Rishabh, As per our last progress meeting, I am off for some days and as now its the time to mid-term evaluation, it would be better to generate a progress report. For that, you should first commit the code as it is and then write 2 to 3 page summary explaining the deliverables so far and then the future plan. Tomorrow is the last day, so better by tomorrow morning, send this across and by

Hello Rishabh, The attached diff file should help you to refactor the existing letor code and plug in your code easily. I have defined the header files with the necessary flow. I have also specified the ranker class, which should be implemented by a new LTR models, ListNet and ListMLE in your case. The evaluation file should be used for validating the performance of the algorithm in the training

Hi, I have several questions regarding the letor module,I looked at the framework of learning to rank in xapian http://rishabhmehrotra.com/gsoc/17.png, I am a little confused. Why using deep learning to find unsupervised features in test data? Since in my understanding, learning to rank model usually learn features from the training data then apply the model to the test data? Why test set and

Hi Rishabh, I think its better not to expose RankiList to Letor.h and make it better user friendly. So my suggestion is to convert RankList to the following statement in this method. std::map<Xapian::docid, double> letor_score(const Xapian::MSet & mset); So just convert the RankList in std::map<Xapian::docid, double> format in the methods where you need to return. Parth. On

Hi Rishabh, I took some time out in the recent days to work on the refactoring. And now it looks like I have included all the files necessary for the complete code. I am sure if it will be quite easy for you now to start with the new code. I would like you to complete it by implementing (copy/paste/little modification) some of the methods. https://github.com/parthg/xapian To make it easier,

Hi all, Thank you for giving me the opportunity to work with Xapian :) I am Jiarong Wei, a third year undergraduate student in Zhejiang University, China. In GSoC 2014, I will work on Letor module with Hanxiao Sun. Here are some questions I encountered these days, 1. In letor.cc, we have two parts of functions: the training part and the ranking part. I?ll use SVMRanker as an example. The

Hi everyone, My name is Shreedhar Pawar. I have already introduced myself on Xapian-discuss... I feel that the Xapian Search/Letor Algorithm, can speed up using Parallel computing. Techniques like Map-reduce, 'compact n split', radix sort, scan, parallel hashing n much more can be used to speed up the learning algorithms as well as the search... support vector machines in the Letor

Dear Sir, I am Pankaj Singhal from Jaipur, India. I am very much interested and strongly looking forward in getting involved in this project Learning-to-Rank. My previous experience in this field is good. Last semester I did a similar job of ranking the URLs of the given huge dataset based on their attribute values. The dataset consisted hundreds of thousands of URLs and each url

Hello, I am Mudit Raj Gupta, fourth year student of M.S. (Hons.) Chemistry and B.E. (Hons.) Electronics and Instrumentation at BITS-Pilani ( http://www.bits-pilani.ac.in/). I am interested in *Machine Learning and Computaional Intelligence*. I have an interest in implementing various existing algorithms and developing modified/new algorithms related to machine learning and computational

Hello Everyone, I am looking forward to contribute to Xapian and also apply as a Google Summer of Code student. I would like to start by introducing myself. I am a final year M.Sc.(H) Chemistry and B.E. (H) Electronics and Instrumentation student at BITS - Pilani, Goa. I am interested in Machine Learning and presently pursuing my thesis on the same. I have been selected for Google Summer of Code

Dear all, My name is Hanxiao Sun and I am a master student in the University of Chinese Academy of Sciences. I am so glad to be selected by Xapian as the GSoC student. This is my first time to work with open source community. I hope I can do a good job with you in this summer ! In my proposal, I followed the scope of the LTR project on the ideas page. But, after the interview, it seems to need

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

1.Could you explain why are these libraries included in all the xapian-letor headers? #include<xapian/intrusive_ptr.h> #include<xapian/types.h> #include<xapian/visibility.h> Or just provide me with the documentation of these header. I looked into these header files but couldn't anything substantial. 2.

As Olly has already pointed out the 2012 branch is not merged. I think there are some compilation errors in the branch. The code in branch is better refactored. The Ranker and FeatureManager classes are well defined and implemented. Parth. On Wed, Sep 25, 2013 at 9:02 AM, Olly Betts <olly at survex.com> wrote: > On Tue, Sep 24, 2013 at 08:34:10PM +0800, jiangwen jiang wrote: >

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 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;

> > > > The approach I was thinking would look something like this: > > * instead of Features, which is really a namespace implemented as a > class, we separate out the calculation of the different features > into distinct subclasses of Feature, whose only job is to calculate > a single feature. Currently the FeatureManager calls these (via >

HI, Parth: Thanks for your reply. There's xapian-letor folder in current master trunk, is this code merged in 2011? the letor code of 2012 is not merged to the trunk? Regards 2013/9/23 Parth Gupta <pargup8 at gmail.com> > Dear Jiangwen Jiang, > > The current state of the project can be reached from the repo: > http://trac.xapian.org/wiki/GSoC2012/LTR > > I would

Hi Rishabh, I had this feeling before. This is a really nice idea BUT we can not go ahead with the project which is still not tested in the experimental settings. Though it may be a wonderful research exercise, I would still vote to go for the state-of-the-art methods which are completely published with full details and experimental results. Hope you get my point. Regards, Parth. On Wed, Apr 4,

Thanks for your reply! For the third question: In https://inex.mmci.uni-saarland.de/data/documentcollection.jsp, I can find inex2010-article.qrels in 2010 assessment, but can?t find query files. Could you send me the link? I have registered on INEX website. And I also need to download ``INEX 2009 collection without annotation tags: (unofficial)`` on