similar to: New to Xapian project

Hey Richhiey, Most probably Xapian is used with CYGWIN in Windows and Windows Specific Code in Xapian is based on CYGWIN, However we would be able to help you out with this issue, if you could pastebin whole 'gnu-make' generated report. Regards, Abhishek On Sat, Jan 3, 2015 at 5:30 PM, <xapian-discuss-request at lists.xapian.org> wrote: > Send Xapian-discuss mailing list

Hello xapian devs, Sorry for not getting back sooner. I was stuck up with coursework. I would like to work on LDA based document modelling and Heimstra's language modelling and would like to form a concrete plan on how to proceed. It would be really helpful if I could have a mentor to assist me with this. Looking forwards to your reply. Thanks. :) -------------- next part -------------- An

Hi all, I am trying to connect Teradata with R using Windows. Due I need to install any specific package or what? I am bit clue-less. Can someone help. Regards, Saj _________________________________________________________________ [[alternative HTML version deleted]]

Hi All I am Manu and recently came across the Xapian project. I will like to contribute to Xapian that gets me introduced to Information Retrieval. I have a basic knowledge of C++. Can you suggest me and help me choose a task that can be good for beginners. Thanks a lot Best Regards Manu Gupta

Hi Olly I will try to work on : http://trac.xapian.org/wiki/GSoCProjectIdeas#Project:LearningtoRank I will be taking a Machine Learning class the next semester and I hope that this project will help me supplement my learning in Machine Learning and also gain a bit of knowledge in IR. If you can give me ideas on how to get around with the code for LTR project, it will be awesome. I can look at

Hello devs, I have filled out the repo link on TRAC as suggested. I'll also keep the journal updated on TRAC from now on. I am almost done with defining all the base classes required for the clusterer and have started coding the euclidian distance metric. This should be completed by tomorrow after which I'll be spending one day to test and make sure everything functions as expected, so

Hello xapian devs, I had shown interest in writing a krovetz stemmer for xapian and spoke to James Aylett about it. Since it was hard to code the stemmer in snowball, I came up with a C++ implementation of the stemmer. But since it is a dictionary based stemmer, im having problems on deciding how to create the dictionary. I did check out some of the implementations of the Krovetz stemmer online

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On Sun, Mar 6, 2016 at 7:17 AM, James Aylett <james-xapian at tartarus.org> wrote: > On Sat, Mar 05, 2016 at 10:58:43PM +0530, Richhiey Thomas wrote: > > K-Means or something related certainly seems like a viable approach, > so what you'll need to do is to come up with a proposal of how you'd > implement this in Xapian (either with reference to the previous work, >

Hello devs, I am Richhiey Thomas, pursuing my third year of undergraduate studies in Computer Science from Mumbai University. I had gone through the project list for this year and the project idea based on clustering caught my attention. I spoke to Assem Chelli on IRC who guided me to the code and got me started. I started going through the code and have successfully built Xapian on my machine.

On 18 Aug 2016, at 23:59, Richhiey Thomas <richhiey.thomas at gmail.com> wrote: > I've currently added a few classes which don't really belong to the public API (currently) into private headers and used PIMPL with the Cluster class. I'm having difficulty reading your changes, because you aren't keeping to one complete change per commit. So for instance you've added a

Hello, I have finished moving the API to PIMPL classes and will fix issues within the current code over the next week, based on reviews from mentors. The next step going forward is to start with forming document vectors that are reduced and more useful. This majorly helps in saving run time (since time for distance calculation depends on number of terms). Getting the useful terms within a

Hello devs. I would like to propose how I plan to go about improving and getting a system that can be integrated into Xapian in this GSoC for the clustering branch. I have identified three areas of work which were not touched last time. 1) Automated Performance Analysis I had roughly implemented 2 evaluation techniques previously (Distance b/w document and centroids within clusters and

On Fri, Apr 08, 2016 at 09:57:16AM -0400, Richhiey Thomas wrote: > Sorry to take so much time on this. Was down with coursework because the > semester end is nearing. Not a problem -- that sort of thing is affecting a lot of people at the moment! > I used the latest development version which is 1.3.5 for this patch. > I have implemented the $match function and it works fine when I

Hey Parth, Thanks for the reply. I am considering implementing a cosine distance metric too, along with euclidian distance because of the dimensionality issue that comes in with K-Means and euclidian distance metric. That does help when we deal with sparse vectors for documents. The particular problem I'm having is representing centroids in an efficient way. For example, when we find the mean

On Mar 29, 2016 4:49 PM, "Olly Betts" <olly at survex.com> wrote: > > On Tue, Mar 29, 2016 at 11:41:02AM +0100, James Aylett wrote: > > It's probably helpful to create a ticket and claim it (and update the > > project ideas list to link to it), so other people don't try to work > > on it as well. (I have a feeling that it might have been among the

Hello devs, My name is Richhiey Thomas.and I've been selected for GSoC 2016 for the project Clustering of Search Results. I would like to thank the Xapian GSoC admin's for giving me this opportunity and James and Olly to help me with my first merge request. In the next two to three days, I'll critically examine all the aspects of the project that I could have any doubts in and clear

Hello, I've been working on the KMeans clustering algorithm recently and since the past week, I have been stuck on a problem which I'm not able to find a solution to. Since we are representing documents as Tf-idf vectors, they are really sparse vectors (a usual corpus can have around 5000 terms). So it gets really difficult to represent these sparse vectors in a way that would be

On Wed, Aug 17, 2016 at 7:23 PM, James Aylett <james-xapian at tartarus.org> wrote: > >> How long does 200?300 documents take to cluster? How does it grow as > more documents are included in the MSet? We'd expect an MSet of 1000 > documents to take longer to cluster than one with 100, but the important > thing is _how_ the time increases as the number of documents

> > > > Actually, you're doing something slightly unusual there: making the > internal member public. Protected would be better, and private is I think > most usual; library clients aren't going to have access to the Internal > class declaration, so they can't call things on it. This means it's > actually difficult right now to subclass Feature. > > I