AND YOU CAN'T REALLY TELL EXACTLY HOW GOOD THAT IS YOU CAN JUST GET AN IDEA THAT IT'S OR THEY USE THE PERPLEXITY ON THE THE LIKELIHOOD TO SAY OH GOOD THIS LIKELIHOOD IS UH IS IT'S SMALLER THAN THE OTHER MM YOU SUGGESTED D USE THE LIKELIHOOD AND PEDRO CAME UP WITH A REALLY GOOD EXAMPLE WHY THAT COULD BE BAD SO YOU HAVE UH YOU HAVE THE UH OH LET ME THING OF WHAT THIS WAS IT WAS TO DO WITH CARS BASICALLY IF YOU HAVE YOU HAVE A TOPIC THAT'S UH REPRESENTING CARS AND YOU CAN TELL THAT THAT'S REPRESENTING CARS BY LOOKING AT THIS DISTRIBUTION AND IT'S THE SAME FOR BOTH NOW YOU WANNA TELL WHICH I I THIS PAGE UH PEDRO'S EXAMPLE OF WHAT IT WAS IS THAT IS SAYS ON THE PAGE LOTUS ELISE OKAY AND THAT UH NO F I CAN'T I JUST REMEMBER IT WAS A REALLY CAN YOU IG REMEMBER WHAT IT WAS OH NO RE NO I DON'T EVEN REMEMBER THE THE YOU SAID I WOULD TELL YOU THAT EVALUATION SHOULD BE DONE BASED ON LIKELIHOOD OR PERPLEXITY YEAH I DIDN'T REALLY CONSIDER DOING IT ON PERPLEXITY ACTUALLY THAT TO BE HON BUT OKAY BUT BUT MAYBE YOU YOU COULD HAVE SOME SOME OTHER LABELLI LI OR THE TASK LIKE IF IF YOU IMAGINE YOU HAVE SOME LABELLING ON OF OF THE WEB PAGES LIKE LIKE LIKE FOR EXAMPLE YOU YOU LOOK AT AT AT AT AT A SET OF PAGES AND YOU HAVE THE M THE DIRECTORY ENTRIES OF THESE PAGES SO SO F LIKE YAHOO OR ENTRIES SO YOU HAVE CATEGORIES AND AND ENTRIES SO FOR EXAMPLE YOU HAVE I DUNNO CARS S. U. V. ETCETERA SO WHAT YOU WOULD LIKE WOULD BE THAT TWO PAGES ON IN THE SAME UM CATEGORY SHOULD BE CLOSER THAN THAN TWO PAGES BEING SPREAD ACROSS DIFFERENT CATEGORIES IS THAT FAIR THOUGH BECAUSE I THINK ONE OF THE THINGS WITH THESE TOPIC MODELS IS THAT YOU DON'T KNOW YOU CAN'T MAKE THEM CLUSTER OKAY AND THEN FOR EXAMPLE YOU YOU YOUR TASK WOULD BE TO SAY I HAVE SOME PAGE AND AND I KNOW WHERE IT IS IN THE IN THE IN THE DIRECTORY AND I HAVE ANOTHER PAGE I DON'T KNOW WHERE IT IS AND I WOULD LIKE TO TO KNOW UH WHETHER IT IS IN THE SAME CATEGORY AS THE FIRST ONE JUST BY COMPARING THEIR UH ASPECTS I IT'S MAKING THE ASSUMPTION THAT UH THIS HUMAN CATEGORISATION IS RELATED TO THE ONE THAT IS DISCOVERED UH MM MM SO BASICALLY WHAT YOU WOULD LIKE TO CHECK IF IS IS IS THERE SOME SIMILARITY IN THE IN THE IN THE ASPECT DISTRIBUTION TELLS ME UH SOMETHING ABOUT UH THE SIM THE THE FACT THAT THEY COULD BE ON THE SAME CATEGORY IN THE THE THIS END END LABEL CATEGORIES YEAH OKAY AND THAT IS IS THAT REALLY FAIR THOUGH CAN YOU SAY THAT IF A SET OF DOCUMENTS IF THE CLUSTERING OF THESE DOCUMENTS IS CLOSER TO THE EFFECTI WHAT YOU WHAT YOU'VE GOT THERE IS UH A CLUSTERING OF DOCUMENTS A AS YOUR DEVALUATION YEAH UH THI THIS THESE LABELS THE YAHOO CATEGORIES THAT'S THAT'S A CLUSTERING SO YOU'RE BY SAYING THAT THIS CLUSTERING IS CLOSER TO THAT CLUSTERING IS IS DOES THAT NECESSARILY MEAN THAT IT'S BETTER HOW WOULD MM-HMM YOU COULD USE THIS TO SAVE TWO DOCUMENTS UH IN THE SAME DIRECTORY OR NOT AND THIS YOU SHOULD BE ABLE TO EVALUATE THEN UM MM-HMM OKAY SO THIS IS A DIRECTORY AND THIS IS SOME SOME SOME SOME WEB PAGE OKAY SO THE LABELLED ONE OKAY AND YOU HAVE SOME PAGE WHICH ARE UNLABELLED BUT YOU HAVE LINKS BETWEEN THOSE TWO SO WHAT WHAT YOU WOULD DO IS THAT YOU WOULD TRY AND P. L. S. A. AND AND UH AND USE A MODEL OVER THAT THEN THEN YOU WOULD LIKE TO FOR EXAMPLE WHAT F WHAT COULD BE VERY SIMPLE WOULD BE JUST TO THEN TO MATCH EACH PAGES LIKE THAT SO LET'S SAY YOU HAVE YOU HAVE A A PAGE WHICH IS LABELLED AND YOU SAY OKAY THE THE LABEL PAGE TWO SHOULD GET SHOULD BE THE ONE W WHICH IT IS THE MOST SIMILAR TO OR ANY KIND OF CLASSIFICATION RULES YOU CAN IMAGINE AND SO AND SO YOU SAY OKAY WHAT WHAT'S IF I FROM FROM THIS PAGE WHICH HAVE THE SIMILAR SO SO THE THE CRITERION WOULD BE TO COMPARE THOSE TWO DISTRIBUTION OKAY AND THEN AND THEN YOU WOULD LIKE TO ASSIGN TO THIS DOCUMENT TOO WHERE YOU DON'T KNOW THE LABELS THE SAME ONE AS THIS ONE AND AND HERE THAT YOU USE ONLY FOR TEST SO THIS IS YOUR THEN YOU CAN EVALUATE HOW WRONG YOU ARE OR CU HOW CLOSE YOU ARE FROM THE REAL ASSIGNMENT THE RIGHT DIRECTORY CATEGORY IN THIS WAY I THINK IT'S FAIR IF YOU KN IF YOU KNOW ONLY IF YOU KNOW ONLY THAT AND THAT AND WHAT YOU WOULD LIKE TO DISCOVER IS THIS THIS IS A R LIKE A REAL TASK LIKE LIKE IF IF IF THIS DIRECTORY UH UH COMPANY WOULD LIKE TO EXTEND THIS DIRECTORY TO NEW PAGES WITHOUT THE HASSLE OF HAVING HUMAN LABELLING BUT IN THIS CASE YOU YOU HAVE TO USE UH THE LABEL ONE YEAH YOUR LOS YOU YOU ONLY HAVE THE LABELS FOR SOME UH SMALL PART OF THE WE UH I THINK YOUR POINT WAS THAT YOU YOU TRAIN THIS WITHOUT LABELLING FIRST YEAH SO YOU YOU WOULD TRAIN IT YOU THIS IS THIS IS T T ALL ALL THOSE LINKS ARE KNOWN THE LINKS BETWEEN SOME LABELLED DOCUMENT AND UNLABELLED DOCUMENT YEAH BUT THE POINT IS THAT YOU SHOULD CHANGE IN A WAY THAT TO TAKE THE LABEL INTO ACCOUNT OR NOT I D I THINK YOU CAN DO IT AS A TWO STEP PROCESS FIRST YOU YOU TRAIN UH WELL MAYBE S IT WOU COULD BE BETTER IF IF IF YOU TAKE IT INTO ACCOUNT BUT BUT MAYBE YOU CAN YOU CAN DO JUST A TWO STEP PROCESS FIRST ONE YOU HAVE THIS UH UNSUPERVISED TASK OVER BOTH P. L. AND P. U. AND THEN YOU FROM THESE UNSUPERVISED STARTS YOU CAN KNOW WHICH DOCUMENT OF P. L. IS CLOSE FROM THE DOCUMENT OF P. U. OR THE REVERSE AND YOU CAN INFER SOME LABEL TO A DOCUMENT OF P. L. YOU CAN TRAIN AFTER THAT UH AN S. V. M. SAYING THIS IS CATEGORY ONE OR TWO ON THE LABEL DOCUMENT AND THEN WE WILL HAVE AN UNLABELLED DOCUMENT AND YOU JUST SAY THIS IS DIRECTORY ONE OR TWO AND IF IT SHOULD IMPROVE IT IF YOU SAY THIS FEATURE EXTRACTION PROCESS IS BETTER THAN YOU CAN HAVE A BETTER CLEANER SEPARATION BETWEEN THOSE TWO WELL TH YEAH THE THE THING THAT WORRIES ME ABOUT THIS APPROACH IS THAT SAY THE REALLY REALLY REALLY SIMPLE EXAMPLE OF THIS WHERE YOUR DIRECTORY HAD TWO CATEGORIES IN IT UH GOOD AND BAD AND AND AND YOU RUN P. L. S. A. ON IT NOW THAT DOESN'T DO IT GOOD AND BAD IT DOES I DUNNO ENGLISH AND FRENCH PAGES