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Matee ( Diese E-Mail-Adresse ist gegen Spambots geschützt! JavaScript muss aktiviert werden, damit sie angezeigt werden kann. ): There are lots of wa

There are lots of ways to build this app. In fact, we were just talking to a customer about building something query refinement by phrase suggestion, which is very similar technically. My fave implementation of this idea is scirus.com (by FAST and Elsevier) which gives you suggestions in “refine your search”.First, do significant phrase extraction. You can either do this per query result set (very expensive, but much better results if you have enough results) or statically (perhaps with updates). Best is to do it versus some background corpus (e.g. Wikipedia), but plain old collocation extraction is OK. Then index the phrases along with the tweets.At run time, when you search, you pull back the sig phrases in the tweets as well as the results, so you get a set of tweets and a tweet-phrase relation. You could either do some kind of fancy dynamic-programming optimization to get an optimal partition by phrase according to some metric (diversity/coherence — see below), or you could just report the top few results and accept some redundancy (realizing that a phrase appearing in all or most hits isn’t useful in organizing results). The real trick for this application is optimizing diversity (low similarity among the clusters) and high coherence (high similarity of tweets within a cluster). Right now, tweemotif’s not doing a very good job of this (clusty.com also has issues — it’s a tough problem). Another thing you might consider for tweetmotif is restricting results to phrases like noun phrases; getting “by the black” is wrong phrasally for a search on the band “Black Keys”, and plain old “-” is just wrong, which I got as a term for search ‘Raveonettes’. And “flu” pulled back “h1n1 flu”, “swine flu”, and “case of h1n1″, which just isn’t diverse enough. I had better luck on the drilldowns for topics like “banh mi”. You should probably also pay attention to Twitter conventions like “#” for tags.

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Davion ( Diese E-Mail-Adresse ist gegen Spambots geschützt! JavaScript muss aktiviert werden, damit sie angezeigt werden kann. ): Another update today

Another update today after ticket follow up (2 updates actually).1st, a Technical Analyst III was able to duplicate the issue as well (which adds further importance, I assume):“…I too am able to replicate this matter. I am investigating this and filing a case immediately. I apologize for the wait and I want to assure you that my aim is to expedite and resolve this issue as soon as possible…”2nd, a follow up after viewing code and the issue at hand, etc.:“…I do apologize, but this was something beyond my ability to correct for you and will need to be addressed by Development. I did go ahead and file a case so you can refer back to this inquiry, 554717, to get further updates on the progress if I have not yet notified you….”The good thing, I think, is that it’s moving up the chain towards resolution; instead of being relegated to trivial status.Looks like it’s past the report stage and is at the case stage.It’s nice to see that cPanel personnel are following up and forwarding to the best people for the job, the developers, so it appears. car insurance in florida rent a car deals

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, could just keep you a live. He was using the term in a military sense; I am using it mheiptoracally in a social-political context. Know who and what you are voting for, for this election is a very important one. May Providence and the U.S. Federal courts save the nation. Godspeed Mr. Berg. I only wish I were in a financial position to contribute to this endeavor to force Obama to answer the questions Mr. Berg has put forth and the msm is incapable of asking. Finances I can not give at this time, if you need signatures for a petition, or a formal letter of complaint, an affirmation of support, please feel free to ask, I for one would be more than willing to assist in that capacity as I'm confident most Americans would if they were aware of the implications of Obamas' non-citizenship and having been nominated for president by the Democratic Party, clearly in violation of constitutional requirements a stipulated by constitutional law.I believe if the court acts in conjunction with constitutional law and not in taking a political stance then the full extent of fraudulent posturing as a U.S. citizen will be exposed. May that time be now!

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There are lots of ways to build this app. In fact, we were just talking to a cmutoser about building something query refinement by phrase suggestion, which is very similar technically. My fave implementation of this idea is scirus.com (by FAST and Elsevier) which gives you suggestions in refine your search .First, do significant phrase extraction. You can either do this per query result set (very expensive, but much better results if you have enough results) or statically (perhaps with updates). Best is to do it versus some background corpus (e.g. Wikipedia), but plain old collocation extraction is OK. Then index the phrases along with the tweets.At run time, when you search, you pull back the sig phrases in the tweets as well as the results, so you get a set of tweets and a tweet-phrase relation. You could either do some kind of fancy dynamic-programming optimization to get an optimal partition by phrase according to some metric (diversity/coherence see below), or you could just report the top few results and accept some redundancy (realizing that a phrase appearing in all or most hits isn't useful in organizing results). The real trick for this application is optimizing diversity (low similarity among the clusters) and high coherence (high similarity of tweets within a cluster). Right now, tweemotif's not doing a very good job of this (clusty.com also has issues it's a tough problem). Another thing you might consider for tweetmotif is restricting results to phrases like noun phrases; getting by the black is wrong phrasally for a search on the band Black Keys , and plain old - is just wrong, which I got as a term for search Raveonettes'. And flu pulled back h1n1 flu , swine flu , and case of h1n1 , which just isn't diverse enough. I had better luck on the drilldowns for topics like banh mi . You should probably also pay attention to Twitter conventions like # for tags. http://tvkbuxdnglm.com [url=http://mvhgzvann.com]mvhgzvann[/url]

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