Sean Owen wrote: > +mahout-user > > From a recommender perspective I can think of three worthwhile projects: > > 1. Combine the two co-occurrence-based distributed recommenders in the > code now. They take slightly different approaches. Ankur's working on > this but might give it over to a GSoC student. This is probably 1/2 > the size of a proper GSoC project. >
Would you tell more about this point? I'm looking at trunk/core/src/main/java/org/apache/mahout/cf/taste/hadoop/cooccurence and I can find only one co-occurrence-based recommender following the path ItemBigraGenerator,ItemSimilarityEstimator,UserItemJoiner,UserItemRecommender. Thanks > 2. Add a fully distributed slope-one recommender. Part of the > computation is already distributed. Efficiently distributing the rest > is interesting. Also not so hard: I'd judge this is 1/2 a GSoC > project. > > 3. Implement a probabilistic model-based recommender of any kind, > distributed or non-distributed. This is probably a whole GSoC project. > > On Fri, Mar 19, 2010 at 11:45 AM, RSJ <i...@richardsimonjust.co.uk> wrote: > >> Hey there, >> >> My name is Richard Just, I'm a final year BSc Applied Computer Science >> student at Reading University, UK, with a strong focus on programming. >> I'm just finishing up a term that included modules in Distributed >> Computing and Evolutionary Computation, which have been the greatest >> modules of my uni career by far. Between that, my love for open source >> and having read about the ASF, I'm really interested in taking part in >> GSoC with an ASF project, namely Mahout. I'm really taken by the ethos >> behind the ASF as a whole and I'm hoping that taking part in GSoC will >> be the start of my long term involvement with ASF projects. >> >> My main programming background is Java, and I did a 9 month placement >> programming in it for a non-profit organisation last year. From that >> placement I gained a love and appreciation for well commented, well >> documented code, while from my time at university I now have a passion >> for well designed code and the time it saves. >> >> With GSoC, I've read through the suggested Mahout projects so far, and I >> think implementing an algorithm is probably my best bet. I say that >> because I don't have much Mahout experience yet, but through multiple >> University modules I do have experience designing and implementing >> algorithms. With that in mind and given that there is already a >> Classifier proposal, I was thinking either a Cluster or Recommendation >> algorithm. >> >> I'd be very interested in hearing if there are any particular Clustering >> algorithms or particular elements of the top Netflix team solutions >> people would like to see implemented? >> >> Many thanks for reading this >> RSJ >> >> > > -- Claudio Martella Digital Technologies Unit Research & Development - Analyst TIS innovation park Via Siemens 19 | Siemensstr. 19 39100 Bolzano | 39100 Bozen Tel. +39 0471 068 123 Fax +39 0471 068 129 claudio.marte...@tis.bz.it http://www.tis.bz.it Short information regarding use of personal data. According to Section 13 of Italian Legislative Decree no. 196 of 30 June 2003, we inform you that we process your personal data in order to fulfil contractual and fiscal obligations and also to send you information regarding our services and events. Your personal data are processed with and without electronic means and by respecting data subjects' rights, fundamental freedoms and dignity, particularly with regard to confidentiality, personal identity and the right to personal data protection. At any time and without formalities you can write an e-mail to priv...@tis.bz.it in order to object the processing of your personal data for the purpose of sending advertising materials and also to exercise the right to access personal data and other rights referred to in Section 7 of Decree 196/2003. The data controller is TIS Techno Innovation Alto Adige, Siemens Street n. 19, Bolzano. You can find the complete information on the web site www.tis.bz.it.
