Go Daddy Operating Company, LLC

Go Daddy Operating, LLC

Wenbo Wang

Wei-Cheng Lai

Chungwei Yen

Yu Tian

Vinit Badrike

Larry Lai

Ankush H Prasad

David Kellogg

Tapan Kamdar

Grace Wardhana

Tejas Prakash Bajaj

Xiang Mao

Anand Krishniyer

Salvador Celis

Jyothiprakash Trishuleshwar

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: receive a character string (e.g., a user input or a file content) from a client; match file tokens tokenized from the character string with knowledge base tokens in a database; generate labels/tags for the file tokens according to labels assigned to the knowledge base tokens and a second level domain (SLD) including a token from the file tokens; remove any tokens from the SLD flagged for removal in the database; generate a top level domain (TLD) and one or more domain names combining the SLD and the TLD; score each of one or more generated domain names according to domain name characteristics; and display a list of scored domain names on the client.

Recommending domains from free text

In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving a request for a plurality of data items from a computing device; determining at least one pattern for at least one metric associated with the computing device; generating at least one digital code based on the at least one pattern meeting a predetermined metric threshold, the at least one digital code comprising access to a plurality of resources; assigning the at least one digital code to the computing device to form at least one assigned digital code; and allowing access to the plurality of resources to facilitate performing a domain name availability determination for the plurality of data items.

Dynamic systems for migrating spam-induced resource starvation domain name search methods of use thereof

A method includes receiving a request for a first domain from a requester with an identification, fetching requester profile using the identification, generating a seed domain based on the request and the requester profile, generating a plurality of SLDs based on the seed domain and the requester profile, generating a plurality of TLDs based on the seed domain and the requester profile, generating a first plurality of candidate domains based on the plurality of SLDs and the plurality of TLDs, generating a second plurality of candidate domains that are currently available by checking the first plurality of domains with a domain registrar, ranking the second plurality of candidate domains to be provided to the requester for a selection, receiving a selected domain, automatically updating the requester profile based on the request and the selection, and fetching the updated profile for generating another seed domain for a subsequent request.

Computer-based real-time relevance systems configured for domain name search personalization and methods of use thereof

Methods are taught for creating training data for a learning algorithm, training the learning algorithm with the training data and using the trained learning algorithm to suggest domain names to users. A domain name registrar may store activities of a user on a registrar website. Preferably, domain name searches, selected suggested domain names and domain names registered to the user are stored as the training data in a training database. The training data may be stored so that earlier activities act as inputs to the learning algorithm while later activities are the expected outputs of the learning algorithm. Once trained, the learning algorithm may receive activities of other users and suggest domain names to the other users based on their activities.

Using a learning algorithm to suggest domain names

Systems and methods of the present invention provide for one or more server computers communicatively coupled to a network and configured to: identify a business name within an aggregation of business names; tokenize the business name; match a resulting token to an industry related keyword; generate a template with placeholders replacing a prefix or a suffix appended to the token from a recognized pattern; identify a request to generate a name candidate, select a personalized data associated with the requesting user and an associated industry; and generate a list of name candidates, with the personalized data inserted into the placeholder; then determines the availability and ranks each name candidate in the list.

Data-driven online business name generator

Training a learning algorithm to suggest domain names

Growing community of inventors

Sunnyvale, CA, United States of America

Wenbo Wang