The proprietary search algorithm of AddSearch is built on top of the leading search platform, Elasticsearch. We score each product based on various factors. In addition to our proprietary search algorithms, we provide features to adjust search ranking.
For example, the following factors affect document ranking:
- Self-learning algorithm: Giving a higher score to documents with better click-through rates
- Sorting: Ranking boosted by defined categories like date, relevancy or other properties
- Pinned Results: Possibility to curate results manually for specific keywords
- Phrase match: Giving a higher score to exact phrase matches. Returning weaker results with lower priority
- Field weights: Products with a keyword match in the title get a higher score than products with a match in the description. Settings can be adjusted manually
- Typo-tolerance: Handling misspelled keywords with fuzzy matching. E.g. “contat information” returns results with the word “contact” properly spelled
- Bigram matching and tokenization: For example, the URL /contact-information/ matches keywords “contact-information”, “contact information” and “contactinformation”
- Synonyms: Possibility to define document-specific or global synonyms. E.g. “coat” matching the word “jacket”
- Partial March, or Wildcards: Return results with a partial search term, e.g. “auto” matching to “automatic”.
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