递归搜索 启发式搜索

This article explores different search techniques, such as collaborative filtering and recommendation engines, along with random and heuristic libraries. It delves into scraping Twitch chat and predicting memes, detecting trending topics or videos using official APIs, recursive searching with filters and updates, topic modeling via Gensim, and identifying fake news in web browsers.

collaborative filtering, recommendation engine

neo4j tutorial on recommendation engine

random search libraries

spotify randomizer

heuristic search libraries

twitch chat scraper and meme prediction heuristic

you can check the same set of video and plot their historical stats, or use official ‘trending’ api to find out.

find ‘random’ videos of certain topic:

search for playlists, collect recommendations

apply to some video feeding apis or official api like giphy

heuristic search, graph search intro

use heuristic recursive search, apply random parameters, find related keywords, apply filters and update weights

topic modeling using gensim

bertopic tutorial can predict topics of new document and get topic similarity

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pip3 install bertopic

可以事先设定好目标 不管这个搜没搜到 都要奖励搜索成功的那次过程 比如老头环和elden ring的对应关系

有没有相关的工具？名字是什么？

recursive text search engine

Heuristic Text Search Engine

free pdf: Heuristic and Systematic Use of Search Engines

it’s like webgpt, which has arxiv pdf paper

openai alignment research is to make artificial general intelligence (AGI) aligned with human values and follow human intent.

there’s also a fake news detector inside web browser

搜索一个词 拿到感兴趣的继续搜下一个

把你搜索的过程记录下来 搜集信息寻找关联的过程记录下来 然后交给ai进行离线训练

同时可以把你创建内容 组织结构的过程记录下来 交给ai离线训练 适用于[template based content generator](./pyjom schedules.md)

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