Abstract: Systems and methods are provided for detecting inaccuracy in a product title, comprising identifying, by running a string algorithm on a title associated with a product, at least one product type associated with the product, predicting, using a machine learning algorithm, at least one product type associated with the product based on the title, detecting an inaccuracy in the title, based on at least one of the identification or the prediction, and outputting, to a remote device, a message indicating that the title comprises the inaccuracy. Running the string algorithm may comprise receiving a set of strings, generating a trie based on the received set of strings, receiving the title, and traversing the generated trie using the title to find a match. Using the machine learning algorithm may comprise identifying words in the title, learning a vector representation for each character n-gram of each word, and summing each character n-gram.

Abstract: A method for generating keywords for searches, comprising the steps of retrieving search metric data comprising a plurality of search strings and interaction data; retrieving a plurality of first product identifiers each having one or more first attributes; generating, a table comprising the plurality of search strings ranked by interaction data; generating relevant lists comprising the plurality of search strings having interaction data above threshold values; retrieving data relating to a second product identifier; extracting one or more second attributes of the second product identifier; performing searches in the relevant lists using the second attribute data; assigning keywords to the data relating to the second identifier.

Abstract: A method for generating keywords for searches, comprising the steps of retrieving search metric data comprising a plurality of search strings and interaction data; retrieving a plurality of first product identifiers each having one or more first attributes; generating, a table comprising the plurality of search strings ranked by interaction data; generating relevant lists comprising the plurality of search strings having interaction data above threshold values; retrieving data relating to a second product identifier; extracting one or more second attributes of the second product identifier; performing searches in the relevant lists using the second attribute data; assigning keywords to the data relating to the second identifier.

Abstract: Systems and methods are provided for detecting inaccuracy in a product title, comprising identifying, by running a string algorithm on a title associated with a product, at least one product type associated with the product, predicting, using a machine learning algorithm, at least one product type associated with the product based on the title, detecting an inaccuracy in the title, based on at least one of the identification or the prediction, and outputting, to a remote device, a message indicating that the title comprises the inaccuracy. Running the string algorithm may comprise receiving a set of strings, generating a trie based on the received set of strings, receiving the title, and traversing the generated trie using the title to find a match. Using the machine learning algorithm may comprise identifying words in the title, learning a vector representation for each character n-gram of each word, and summing each character n-gram.

Abstract: A method for generating keywords for searches, comprising the steps of retrieving search metric data comprising a plurality of search strings and interaction data; retrieving a plurality of first product identifiers each having one or more first attributes; generating, a table comprising the plurality of search strings ranked by interaction data; generating relevant lists comprising the plurality of search strings having interaction data above threshold values; retrieving data relating to a second product identifier; extracting one or more second attributes of the second product identifier; performing searches in the relevant lists using the second attribute data; assigning keywords to the data relating to the second identifier.