On Tue, Jun 20, 2017 at 12:07 AM, Linas Vepstas <[email protected]> wrote: > So again, this is not where the action is. What we need is accurate, > high-performance, non-ad-hoc clustering. I guess I'm ready to accept > agglomerative clustering, if there's nothing else that's simpler, better.
We don't need just clustering, we need clustering together with sense disambiguation... I believe that we will get better clustering (and better clustering-coupled-with-disambiguation) results out of the vectors Adagram produces, than out of the sparse vectors you're now trying to cluster.... But this is an empirical issue, we can try both and see... As for the corpus size, I mean, in a bigger corpus "He" and "There" (with caps) would also not come out as so similar.... But yes, the list of "very similar word pairs" you give is cool and impressive.... It would be interesting to try EM clustering, or maybe a variant like this, https://cran.r-project.org/web/packages/HDclassif/index.html on your feature vectors .... We will try this on features we export ourselves, it if we can get the language learning pipeline working correctly.... (I know we could just take the feature vectors you have produced and play with them, but I would really like us to be able to get the language learning pipeline working adequately in Hong Kong -- obviously, as you know, this is an important project and we can't have it in "it works on my machine" status ...) I would like to try EM and variants on both your raw feature vectors, and on reduced/disambiguated feature vectors that modified-Adagram spits out based on your MST parse trees.... It will be interesting to compare the clusters obtained from these two approaches... -- Ben -- Ben Goertzel, PhD http://goertzel.org "I am God! I am nothing, I'm play, I am freedom, I am life. I am the boundary, I am the peak." -- Alexander Scriabin -- You received this message because you are subscribed to the Google Groups "opencog" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/opencog. To view this discussion on the web visit https://groups.google.com/d/msgid/opencog/CACYTDBdjkj1KqmZsTpEWi2bTwhE0L5rky_Cd5ZV_6bdQwLbjFw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
