imperium's People
imperium's Issues
Similarity Search
Overview:
- Split the sentence to words.
- return URL for expression.
Tasks: (similarity metric -> 0 for perfect match)
- Precompute maximum length of phrase.
- greedily search for word-combination (max: max-phrase-length) having minimum distance from the centroid.
- each time vectorize the combination.
- find the closest semantically closest word of the new formed phrase / word.
- For proper nouns, check if present in dictionary. else, fingerspell.
NOTE: Don't count the stop words.
API Design Overview:
-
class SimSearch
: properties-> vectorizer, clusterDB, dictVectDB, MAX_LENGTH_PHRASE (from config) -
simSearch.splitTokens(sentence)
: iterates over each consecutive word combination and keeps track of minimum distance from the center. stop at MAX_PHRASE_LENGTH / ProperNoun reached, which ever earlier. -
simSearch.tagPOS(word)
: Helper function for pos tagging. -
simSearch.queryVideoClip(token)
: Query DB to obtain video clip from token. -
simSearch.fingerspell(character_token)
: helper function to fingerspell mp4 of thecharacter_token
. -
simSearch.query(setence)
: Stitch everything together and return list of video links. (in-order)
NOTE: Can be made faster by creating parallel jobs to work on splices of length MAX_LENGTH_PHRASE. if stopped before MAX_LENGTH_PHRASE, can be kept in a Queue with a position index in the token list.
Video Scraping
- scraper to extract video URLs
- string search to extract query words from URL
- Redis integrator.
NOTE: Redis is used for fast (Key, Value)
storage and extraction, where Key
= Word to search for, Value
= URL for Video
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