Find matching documents, customers, profiles and more.
Train your own custom-built match scoring algorithm.
Why search when you can match?
Matching is different to searching. Match queries comprise much richer information than typical search. Dating apps use attributes/preferences of people to match them together, HR uses matching to predict how well a job applicant’s resume matches a job vacancy, banks use matching to predict fraud patterns. Matching is increasingly driving the world around you, Sajari puts that power in your forearms.
For many applications, Sajari permits the creation of fully custom-made match scores based on any object attributes. Sajari has built in features to compare numbers, lists, categories, free text, location and more. Any attribute can be weighted in your match score, the weightings can even be derived for you! See our use cases.
Configure your own matching algorithm using machine learning, geolocation, meta matching and more.
Leverage machine learning data extraction and classification in your match algorithms.
Find close matches using your own custom-built scoring algorithm. Or compare and score pairs of items one-to-one.
Your match score configuration can also integrate structured data, such as price, time, locations, categories, machine learning classifiers and much more.
Sajari can also use training data to create your match score for you. This process analyses the text and meta information of your data and then uses multivariable regression and random forest algorithms to create a match score configuration that best replicates your training data.
Complicated queries made effortless
Typical search technology was not made to process queries composed of hundreds of keywords, meta information, machine learning classifiers and more. Sajari was designed exactly for this, and it’s utterly quick.
If you need to find the best matches in your content using many structured attributes and/or unstructured text, then Sajari is most likely a superb match for your application. If you need assistance to get up and running, we are here to help. Contact us today for more details.
Custom-made Match algorithms
Below is a sample result item from a match style search query. In this case the input query was enriched with meta information such as lat-lng, salary, a list of abilities etc. The match algorithm was configured to compare meta information in a multiplicity of ways (for more info see the match configuration settings), each of these configured comparisons is returned in the result calculation component of the response.
Effectively this permits you to play with the importance of each matching algorithm component and have all your results re-ordered in realtime. Is location more importance than salary difference? Is a skill overlap significant or just desirable? How significant is connection overlap? etc.
We have applications using “people you may know” style matches based on university attended, age and connection overlap, another asks questions to find people with closely matching pysch profiles, yet another is designed to find similar staff. The use cases are endless, use your imagination! Whatever information you have can be used to create your own match algorithm!
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