OK, I decided to implement SVM because it would be useful for professor from my college, who works at his SE. How much is probabitity to my application be accepted?
Greetings --- Ted Dunning <[EMAIL PROTECTED]> wrote: > > SVM is fine but can be very expensive (and complex) > for training especially > for text-like applications. Regularized logistic > regression can be just > about as good for document classification and is > much easier to implement. > I suspect that random forests would work very well > as well. > > As a GSOC project, SVM would be a good thing to > implement for mahout. So > would all of the other algorithms. > > > On 3/29/08 10:47 AM, "Marko Novakovic" > <[EMAIL PROTECTED]> wrote: > > > I collabotate with one proffesor form my faculty, > > whose phd thesis was about machine learning in > SE-s. > > He uses combination of Naive Bayes and SVM. I > didn't > > understand his solution enough. > > But I think that SVM is very useful and deployable > > algorithm for SE-s. > > Do you think that I should change anything in my > > application. > > > > Greetings > > > > --- Ted Dunning <[EMAIL PROTECTED]> wrote: > > > >> > >> SVM is not the only solution to these problems. > For > >> many search engine > >> applications, it isn't even likely to be the > best. > >> Regularized logistic > >> regression is a strong candidate as are random > >> forests and boosted trees. > >> > >> Beware of any author who claims that their > algorithm > >> for machine learning > >> that claims to be better than all others. The > >> algorithm may well have some > >> virtues, but it is unlikely to be universal. It > is > >> more likely that the > >> author who claims this simply has a limited view > of > >> the range of things that > >> might need to be done. > >> > >> > >> On 3/29/08 10:23 AM, "Marko Novakovic" > >> <[EMAIL PROTECTED]> wrote: > >> > >>> The implementation of SVM algorithm at Hadoop > >> platform > >>> > >>> Abstract: > >>> > >>> I have been researching in Search Engines > >>> functionalities, like ranking, presenting > relevant > >>> page to users, etc. > >>> I noted that the most usable solution for search > >>> engines is Support Vector Machine. > >>> The best solution for determination relevant > page > >>> ranking for user based search result is SVM. > >>> Reference to this problem is article: > >>> T. Joachims, F. Radlinski: "Search Engines that > >>> Laerning from Implicit Feedback," IEEE Computer, > >>> August 2007, pp 38 > >>> According to SVM is very complex algorithm, > which > >> has > >>> a lot of operations, > >>> I decided to implement SVM algorithm at Hadoop > >>> platform. > >>> > >>> Dear Apache, > >>> > >>> My Idea: > >>> > >>> I have idea to implement model and solution for > >>> retrieving relevant ranking Web pages driven by > >> user's > >>> past behavior. > >>> According to SE-s have a lot of crawled Web > pages, > >>> this operation must be realized distributed if > we > >> want > >>> to obtain results in real time and have fresh > >> learned > >>> database. > >>> So we should paralelize all algorithms, which > are > >> used > >>> for processing Web pages. > >>> So I decided to implement the most used and > >> exploited > >>> algorithm in machine learning, deployed in > >> operating > >>> Web pages. > >>> I also, choose SVM algorithm because it is very > >>> complex algorithm for implementation > >>> and I like temptations and I am not affraid of > >> hard > >>> tasks. > >>> I tend to achieve most a big degree of > >> performances > >>> through paralelization. > >>> I will exploit working on this project for > writing > >> new > >>> article about deployment of clustering at SE-a. > >>> I have prepared to this project reading > articles: > >>> [1] C. Burges, "A Tutorial on Suppot Vector > >> Machines > >>> for Pattern Recognition," Kluwer Academin > >> Publishers, > >>> Boston > >>> [2] R.E Fan, P.H Chen, C.J. Lin, "Working Set > >>> Selection Using Second Order Information for > >> Training > >>> Support Vector Machines," Journal of Machine > >> Learning > >>> Research 6 (2005), pp 18891918 > >>> I also have read Hadoop documentation and > examined > >>> your implementations of algoritm kMeans at this > >>> platform. > >>> > >>> Methodoligies of Development: > >>> > >>> - Test Driven Development > >>> - Deployment ANT an JUnit > >>> - SDK: Eclipse > >>> - SVN System for Versioning > >>> - Javadoc > >>> > >>> About Me: > >>> > >>> My resume you can see at link > >>> http://atisha34.googlepages.com/. > >>> I also participate in some academic projects at > my > >>> college: > >>> - Working at topic based Search Engine, called > >> Grain, > >>> which is in construction at my faculty. > >>> - Tutorial about SE-s, mentored by professor > >> Veljko > >>> Milutinovic: "The New Avenues in Search Engines" > >>> presentation: > >>> > http://atisha34.googlepages.com/Searchengines.ppt > >>> abstract: > >>> > >> > > > http://atisha34.googlepages.com/TheNewAvenuesinWebSearch.docx > >>> I should publish article driven by this > >> presentation > >>> at IPSI Magazine. > >>> - Other projects in which I participate aren't > >> related > >>> to machine learning and search engines. > >>> > >>> My Interests: > >>> - Search Engines > >>> - Software Engineering and Test Driven > Development > >>> - Machine Learning > >>> - Database Modeling and OO Design > >>> - ERP and Business Processes > >>> > >>> Sincerely Yours, > >>> Marko Novakovic > >>> > >>> --- Karl Wettin <[EMAIL PROTECTED]> wrote: > >>> > >>>> Marko Novakovic skrev: > >>>> > >>>> Hi Marko, > >>>> > >>>>> I apply for SVM algorithm at Hadoop platform. > >>>>> I hope that I will be accepted by Google and > >>>> Appache, > >>>>> I am serious in intention to do this jos as > >> great. > >>>> > >>>> great news! Feel free to post your proposal > here > === message truncated === ____________________________________________________________________________________ OMG, Sweet deal for Yahoo! users/friends:Get A Month of Blockbuster Total Access, No Cost. W00t http://tc.deals.yahoo.com/tc/blockbuster/text2.com
