Verisign, Inc.

Vincent Raemy

Jean Hennebert

Baptiste Wicht

Aubry Cholleton

Vincenzo Russo

Neel Goyal

Harshini Ramnath Krishnan

Andreas Fischer

Yannis Labrou

Andrew West

Techniques for generating unregistered internet domain names using machine learning (e.g., neural networks) are presented. The techniques can include identifying, using an electronic processor, a subset of registered domain names having at least one specified characteristic, vectorizing, using an electronic processor, a training subset of domain names in the subset of registered domain names to obtain a set of vectors, training, using an electronic processor, a machine learning algorithm with the set of vectors to produce a trained machine learning model, generating, using an electronic processor, at least one output domain name by the trained machine learning model, and outputting the at least one output domain name.

Deep neural network generation of domain names

Embodiments relate to systems, devices, and computing-implemented methods for generating domain name suggestions by obtaining a domain name suggestion input that includes textual data, segmenting the textual data into tokens, obtaining a list of possible affixes to the textual data, determining conditional probabilities for the possible affixes using a language model, ranking the list of possible affixes based on the conditional probabilities to generate a ranked list of affixes, and generating domain name suggestions based on the ranked list of affixes.

Systems, devices, and methods for improved affix-based domain name suggestion

Techniques for generating internet domain name suggestions using machine learning are presented. Some techniques include obtaining sets of domain names, each set of domain names including domain names that concern a selected topic, training machine learning algorithms, such that trained language models are produced, each trained language model concerning a different selected topic, obtaining a seed domain name, identifying a primary topic that the seed domain name concerns, applying to the seed domain name a trained language model of the trained language models that concerns the primary topic, such that a primary proposed domain name is produced, where the primary proposed domain name concerns the primary topic and includes the seed domain name and at least one of a prefix or a suffix, and offering to register the primary proposed domain name.

Provided are methods, devices, and computer-readable media for accessing a domain name; determining, via the processor, at least two words in the domain name; determining at least one alternative word for at least one word in the domain name; determining whether the at least one alternative word is contextually relevant; and generating at least one alternative domain name based on a determination that the at least one alternative word is contextually relevant.

Syntactically and/or semantically relevant alternative domain name generation

A system, method, and computer-readable medium, is described that implements a resource navigation links tool that receives one or more inputs, extracts information from the inputs into a submission string, submits the submission string to a resource navigation links tool, and receives resource navigation links based on the submission string. Inputs types may include images, audio clips, and metadata. The inputs sources may be processed to extract information related to the image source to build the submission string.

Image, audio, and metadata inputs for domain name suggestions

Provided are methods, devices, and computer-readable media for generating a string of characters based on a set of rules; parsing the string of characters into string of graphemes; determining one or more phonetic representations for one or more graphemes in the string of graphemes based on a first data structure; determining at least one grapheme representation for one or more of the one or more phonetic representations based on a second data structure; and constructing the phonetic representation of the string of characters based on the grapheme representation that was determined.

Construction of a phonetic representation of a generated string of characters

Provided is a method, device, and computer-readable medium for converting a string of characters in a first language into a phonetic representation of a second language using a first data structure that maps graphemes in the first language to one or more universal phonetic representations based on an international phonetic alphabet, wherein the first data structure comprises a plurality of first nodes with each first node of the plurality of first nodes having a respective weight assigned that corresponds to a likely pronunciation of a grapheme, and a second data structure that maps the one or more universal phonetic representations to one or more graphemes in the second language, wherein the second data structure comprises a plurality of second nodes with each second node of the plurality of second nodes having a respective weight assigned that corresponds to a likely representation of a grapheme in the second language.

Method for writing a foreign language in a pseudo language phonetically resembling native language of the speaker

A method can include receiving, from a user, a string of characters. The method can also include determining components of the string of characters. The components of the string of characters may include one or more graphemes that are related in the string of characters. The method can include determining universal phonetic representations for the components of the string of characters. The method can also include determining pronunciations for the universal phonetic representations. Additionally, the method can include constructing a pronunciation of the string of characters based at least partially on the pronunciations of the universal phonetic representations. Further, the method can include sending, to the user, a sound file representing the pronunciation of the string of characters.

Systems and methods for automatic phonetization of domain names

Provided are methods, devices, and computer-readable media for accessing a string of characters; parsing the string of characters into string of graphemes; determining one or more phonetic representations for one or more graphemes in the string of graphemes based on a first data structure; determining at least one grapheme representation for one or more of the one or more phonetic representations based on a second data structure; and constructing the phonetic representation of the string of characters based on the grapheme representation that was determined.

Construction of phonetic representation of a string of characters

Image, audio, and metadata inputs for keyword resource navigation links

A system, method, and computer-readable medium, is described that implements a domain name registration suggestion tool that receives one or more inputs, extracts information from the inputs into a submission string, submits the submission string to a domain name suggestion tool, and receives domain name suggestions based on the submission string. Inputs types may include images, audio clips, and metadata. The inputs sources may be processed to extract information related to the image source to build the submission string.

Image, audio, and metadata inputs for name suggestion

A method for generating a bigram database may include receiving domain names, tokenizing the domain names, generating token bigrams from the tokenized domain names, filtering the token bigrams, ranking the token bigrams, and storing the filtered and ranked token bigrams in a bigram database. A method for suggesting alternative domain names may include receiving a requested domain name, tokenizing the requested domain name to divide the requested domain name into a series of tokens, retrieving token bigrams for tokens of the requested domain name, generating alternative domain name suggestions based on the token bigrams and the requested domain name, ranking the alternative domain name suggestions, and outputting at least one of the alternative domain name suggestions.

Growing community of inventors

Fribourg, Switzerland

Vincent Raemy