Abstract: One aspect of the present disclosure is directed to a computer-implemented system for streamlined product searching configured to receive a search query comprising at least one keyword; determine a product type; retrieve a first record of products associated with the product type; determine whether the search query meets a condition; and if the search query meets the condition: determine, a plurality of label values, and for each label value: generate a second record of products associated with the label value; determine whether each product in the second record meets a condition; deleting each product that meets the condition from the second record; ranking each remaining product in each second record; display the plurality of label values for selection; receive a selected label value; and display at least a portion of the remaining ranked products associated with the selected label value.

Abstract: A computerized system and method for dynamically generating modified user interface is disclosed. The method comprises receiving a search request, providing a list of at least one product in response to the search request, receiving a selection of a first product from the user device, providing the first product to the user device for display on the user interface, determining signals of the first product and their weights, calculating a score for each of the second products based on signals of the first product, ranking the second products by the score, and in response to receiving a request to redisplay the list of product, providing, to the user device for display together with the list of product, at least one second product based on the ranking.

Abstract: Disclosed embodiments provide systems and methods for generating and presenting relevant product search results based on a user past purchase history. A method generating and presenting product search results based on past purchase history comprises retrieving a user product search query, a set of historical purchase data associated with the user, and a set of experimental data comprising a hierarchical list of product categories. The method further comprises determining a list of queried product categories based on a plurality of attributes and the pattern using machine learning algorithms. The method further comprises generating a hierarchical list of historical product categories associated with the user. The method further comprises generating a list of product search results associated with the user's product query. The method further comprises ranking the list of product search results based on the user's past purchase history and presenting the ranked list of product search results to the user.

Abstract: One aspect of the present disclosure is directed to a computer-implemented method for streamlined product searching. The method may include receiving a search query comprising at least one keyword; generating a listing of related products based on the keyword; ranking each related product based on applicability; determining a product type of at least the highest ranking related product; determining a filter sequence associated with the product type; generating a first record comprising the filter sequence; instantiating a second record of selected attributes; displaying a first filter in the filter sequence; receiving a first selected attribute from the first filter; displaying the second filter; receiving a second selected attribute from the second filter; and displaying a listing of products associated with the selected attributes in the second record.

Abstract: One aspect of the present disclosure is directed to a computer-implemented system for streamlined product searching configured to receive a search query comprising at least one keyword; determine a product type; retrieve a first record of products associated with the product type; determine whether the search query meets a condition; and if the search query meets the condition: determine, a plurality of label values, and for each label value: generate a second record of products associated with the label value; determine whether each product in the second record meets a condition; deleting each product that meets the condition from the second record; ranking each remaining product in each second record; display the plurality of label values for selection; receive a selected label value; and display at least a portion of the remaining ranked products associated with the selected label value.

Abstract: One aspect of the present disclosure is directed to a computer-implemented method for streamlined product searching. The method may include receiving a search query comprising at least one keyword; generating a listing of related products based on the keyword; ranking each related product based on applicability; determining a product type of at least the highest ranking related product; determining a filter sequence associated with the product type; generating a first record comprising the filter sequence; instantiating a second record of selected attributes; displaying a first filter in the filter sequence; receiving a first selected attribute from the first filter; displaying the second filter; receiving a second selected attribute from the second filter; and displaying a listing of products associated with the selected attributes in the second record.