Recommendation systems and methods using interest correlation

摘要

A search technology generates recommendations with minimal user data and participation, and provides better interpretation of user data, such as popularity, thus obtaining breadth and quality in recommendations. It is sensitive to the semantic content of natural language terms and lets users briefly describe the intended recipient (i.e., interests, eccentricities, previously successful gifts). Based on that input, the recommendation software system and method determines the meaning of the entered terms and creatively discover connections to gift recommendations from the vast array of possibilities. The user may then make a selection from these recommendations. The search/recommendation engine allows the user to find gifts through connections that are not limited to previously available information on the Internet. Thus, interests can be connected to buying behavior by relating terms to respective items.

主权项

1. A computer implemented method of recommending products and services comprising the steps of:
processing media content and a plurality of user generated profiles to extract keywords; generating a corpus of keywords using the extracted keywords; identifying which keywords from the corpus commonly co-occur in the user generated profiles and media content; and expanding a search query with additional search terms related to the search query, where the additional search terms are determined using one or more of the identified co-occurring keywords and by determining a correlation index between one or more terms of the search query and one or more keywords from the corpus, wherein the additional search terms have a correlation index above a threshold.