Features Enhancement for Ecommerce Search

Allow customers to find exactly what they want with improved search results.

The need for structured data extends to all kinds of search, be it standard free-text search or new-generation voice search. In ecommerce, that implies every laptop in your catalog needs to have its screen-size expressed in inches and every shirt needs the right color tag. Without relevant information it is difficult for consumers to find exactly what they need.

Our Feature Enhancement API fulfills this need using a combination of methodically curated taxonomies, artificial intelligence techniques and strategically inserted heuristics.

Key standardizaion

Key Standardization to maps all attribute names to our standardized taxonomy.

Display size: 13 inches
screensize 13in

Approximate size is 2 inches x 3 inches x 4 inches
length 2in
width 3in
height 4in

Average Battery Life: 8 hours
batterylife 8 hours

Named Entity Recognition

Named Entity Recognition to extract structured key-value pairs from unstructured fields such as product title and description.

Description: This laptop has an Intel Core i7 processor
processortype Intel Core i7

Name: Minnie Mouse Toy by Disney
character Minnie Mouse

Description: Painting by Van Gogh from the year 1831
artist Van Gogh
year 1831

Value Normalization

Value Normalization to map attribute values of selective fields to comparable formats.

length: 2in, width: 3in, height: 4in
length 50.8mm
width 76.2mm
height 101.6mm

weight: 1lbs
weight 453592mg

OS: mac osx v10.9
operatingsystem Mac OS X v10.9

How to get setup

Tell us the categories and features/attributes you’re interested in. Next, send us the dataset you’d like standardized and normalized. If you don’t have your own dataset, tell us what kind of data you’re looking for.

After a brief consultation, our technical leads map your category-attribute list to our internal taxonomy. Then, start testing our algorithms with a Pilot or Proof-of-Concept.

Semantics3 products in this solution