đŸȘŽ Quartz 4.0

pKeicho

Aug 20, 20217 min read

Kanban in Scrapbox

pKeicho202103-202104done

Memo - End Design - In the derivation, “[Allow questions to create command buttons. - Conversation log 2021-01-30 - I think the endgame of this one is probably that after the mode transitions to asking about relationships between symbols because it has a lot of keywords and considers them developed enough, it runs out of high scoring words, but it’s still in the asking about relationships mode. - Perhaps judging it from the distribution of keyword scores, - I propose an end. - Propose a new chat. - Return to search mode - I think it would be appropriate to do one of the following - question naturalness data set - The amount of features should be improved. - Related: Tuning questions that take two arguments. - Do not repeat symmetrical questions: done - Need to collect naturalness for questions that take two arguments as well. - Related: Good and bad feedback during conversation. - NG feedback is used as training data - → Not enough data and poor quality as training data. - I think I’d be better off teaching through active learning.

- [[One-click import to Regroup]]
- [[IGNORE file to exclude inappropriate items from the analysis]]
- (e.g., logs that are not being used properly)
- [[Feedback button: Like]]

  • Do not tamper with the score to represent the subject of interest.

  • In response to the input “Tsu, Tsuyoshi”.

    • Not selected as a keyword because “strong” is an adjective.
      • “What kind of “tough” is that “tough”?” is an ant question, so you might want to extract it.
    • The â€œă€â€ can be a noun, so it is included in the keywords.
    • The result is that you end up asking “one” digging question.

  • Play keywords that are not good.

    • The CUI version had.
    • Turn it off when you make the Mattermost version and keep it off.
    • Use NGKW feedback to learn!
    • →There are quite a few cases where users are unaware of NGKW even though it’s a good keyword, and learning from users makes you a fool.
      • I put it in the form of putting only the obvious no-no’s on the list.

  • What we want to feedback

    • Keyword extraction is not the first step.

      • You’re starting to buy into the subtlety of it.

      • Where is that w?

      • NGKW command.
    • NG keywords selected for input
      • Example: The - midday sun
      • Keyword extraction is fine, but not in the direction the user wants to drill down
        • I hope you can say, “No, not that way,” because this might not be something you can learn about in advance.
        • It was realized in the form of the NGKW and UPKW commands.
    • Not a good combination of keywords and questions chosen.
      • NG feedback is used as training data
    • Identical symbol relationship

    • If the answer is that the relationship between two symbols is identical, it’s not a good idea to ask questions about the relationship between symbols.

    • Wouldn’t it be nice if a button appeared that said “same” and when you pressed it, the two keywords were merged as a command?
      • I’ll test it properly, because I’m afraid that the disappearance of one of the keywords might cause some bug.

  • State Transition Mechanism

  • Include attenuation in cumulative score calculation?

    • Wouldn’t it be better to add attenuation? I’ve wondered about that.
    • On the other hand, I’m also inclined to think that if you’re responding well to the first “what do you hope will happen in this dialogue”, you might want to remind yourself of the key words there from time to time.
      • Often we observe cases where the first answer on this is messy.
      • It’s quite common for people to get more organized as they talk and it becomes clearer what they were looking for, so don’t put too much emphasis on the first statement


  • write_learning_pair

    • Hypothesis that questions that provoke long user input are good questions
    • Questions that do not take keywords should take features from env.
    • No means of recovery if keywords are split
    • Judgment of Awareness
    • Early design
    • Someone is making utterances that do not contain keywords on the first move. Now I’m asking questions without keywords anyway to avoid errors, but I might as well direct them to help since they don’t seem to understand how to use it in the first place.
    • If you cut too much with NGKW before the keywords are developed, the “fountain has dried up”.
      • Maybe we are in a vicious cycle of using NGKW so much that the keywords are depleted, the program jumps to a keyword from the most recent statement and asks a question, which is off the main topic, so it is NGKWed again.
      • How can we successfully lead them to the state of being crowded with lots of keywords?
      • Show the percentage of the value to be achieved in each phase?
      • Point out that there are too few keywords and the pace of NGKW is too fast?
        • We could make it so that when there are few keywords, you have to wait a bit before you can press the button.

  • It would be nice if questions could specify some of the answers.

    • Is it the same? No?” displays the “Same” button
      • When selected, it functions as a merge command for keywords.
    • Is this a good place to end?” should be “yes” or “no”.
      • That selection can be used directly for training data.

  • ppoi

    • Read back and update

  • Add a RAKE-like element to keyword extraction

    • Extract long sequences that appear in your own past statements/past logs/Scrapbox

  • pKeicho-done-2021-02-05

Keichobot History

This is software that helps you verbalize and retrieve “what is already in you but not yet verbalized” and is not intended to give you answers to your questions.

Keywords:.chatbot nisbot.icon

pKeicho-done Don’t we need pairs of input rows and keyword extraction results? →done

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