Thanks! I'll try with (a) and maybe some Dirichlet Process Clustering. I notice that LDA needs also maxWords. In my understanding that's the length of the dictionary.txt (the number of unique words in my vectors) i got from lucene.vectors. Is that correct?
Ted Dunning wrote: > This is a difficult topic that is addressed in different ways in practical > situations. The approaches I know of include: > > a) just pick a number that is probably big enough and go forward. 20, 30, > 50 or 100 are all viable choices depending on the scale of your corpus. > Numbers as small as 5 might make sense for special purpose cases such as > voting histories. > > b) run a parameter sweep over the number of topics and look at posterior > likelihood of your corpus. This is pretty commonly done. > > c) move to a more advanced non-parametric Bayesian approach where your > learning algorithms basically to (b) in a single learning process. I > haven't heard of anyone doing this in applied situations yet, but it is a > very seductive goal. > > Only (a) and (b) are viable in Mahout's implementation of LDA. Option (c) > is implemented in our Dirichlet Process clustering, but that is less > powerful in some ways than LDA. > > On Thu, Mar 4, 2010 at 6:56 AM, Claudio Martella <[email protected] > >> wrote: >> > > >> The documents span different topics and i don't know in advance >> (and would LOVE to avoid it) their number. Do you have any advice on a >> strategy to follow? >> >> > > > > -- 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 [email protected] 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 [email protected] 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.
