Abstract: A set of first results from a first query are received. Using a natural language processing technique, a set of second results using a second query having at least a portion of the first query and at least a portion of set of first results are generated, wherein the natural language processing technique comprises a machine learning model configured to analyze the set of first results. The set of second results are scored based upon a semantic comparison of the set of first results, the second query, and the set of second results. Using the scored set of the second results, a set of processed results are generated.

Abstract: A filter assembly including a filter screen (27) comprising a band (27?) of porous material extending between two axially aligned opposing ends (38, 38?) and defining a cylindrical periphery (29), wherein the ends (38, 38?) are each secured to a dynamic tensioning mechanism (46) that permits the ends (38, 38?) to move bi-directionally relative to one another about the periphery (29) of the filter screen (27).

Abstract: A system for online conversion attribution. The system includes a short uniform resource locator (URL) service programmed to, in response to receiving a short URL from a device: provide a cookie that includes a short URL ID to the device, and provide a short URL descriptor including the short URL ID to a user mapping service. The system further includes the user mapping service programmed to receive the short URL descriptor, receive a social media descriptor including a social media ID, map the short URL ID to the social media ID using the short URL descriptor and the social media descriptor, and attribute, using the mapping, a conversion on a website accessed using the device based upon receipt of the short URL ID from the device.

Abstract: A method and system for managing a search is disclosed. The method and system can include receiving a set of first results from a first query. A set of categories can be identified based on the set of first results. The method and system can include generating a set of second results using a second query having at least a portion of the first query, at least a portion of the first results, and at least a portion of the set of categories. The method and system can also include scoring the set of second results based upon a relationship of the first query, the second query, and the set of second results.

Abstract: Some embodiments include a method of facilitating item selection based on features. Other embodiments of related systems and methods are also disclosed.

Abstract: A method and system for managing a search is disclosed. The method and system can include receiving a set of first results from a first query. A set of categories can be identified based on the set of first results. The method and system can include generating a set of second results using a second query having at least a portion of the first query, at least a portion of the first results, and at least a portion of the set of categories. The method and system can also include scoring the set of second results based upon a relationship of the first query, the second query, and the set of second results.

Abstract: A filter assembly including a filter screen (27) comprising a band (27?) of porous material extending between two axially aligned opposing ends (38, 38?) and defining a cylindrical periphery (29), wherein the ends (38, 38?) are each secured to a dynamic tensioning mechanism (46) that permits the ends (38, 38?) to move bi-directionally relative to one another about the periphery (29) of the filter screen (27).

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A system, method, and computer-readable storage media, having computer-executable instructions embodied thereon, for organizing and describing product information is provided. The system includes a memory device, an IDML module, and a display module. The memory device is configured to store product data in a plurality of product records. Each product record is associated with an associated one of a plurality of products and has an associated product type. The product records provide may be used to the efficient storage, processing and exchange of product information. The IDML module is configured to receive a product request and receive, from the memory device, results data associated with the product request. The results data includes a plurality of product records. The display module receives the results data and responsively displays the results data associated with the product request.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A computer processor determines a first span of a communication, wherein a span includes content associated with one or more dialog statements. If the content of the first span contains one or more topic change indicators which are identified by at least one detector of a learning model, the computer processor, in response, generates scores for each of the one or more indicators. The computer processor aggregates scores of the one or more indicators of the first span, which may be weighted, to produce an aggregate score. The computer processor compares the aggregate score to a threshold value, wherein the threshold value is determined during training of the learning model, and the computer processor, in response to the aggregate score crossing the threshold value, determines a topic change has occurred within the first span.

Abstract: A method and system for managing a search is disclosed. The method and system can include receiving a set of first results from a first query. A set of categories can be identified based on the set of first results. The method and system can include generating a set of second results using a second query having at least a portion of the first query, at least a portion of the first results, and at least a portion of the set of categories. The method and system can also include scoring the set of second results based upon a relationship of the first query, the second query, and the set of second results.

Abstract: A method and system for managing a search is disclosed. The method and system can include receiving a set of first results from a first query. A set of categories can be identified based on the set of first results. The method and system can include generating a set of second results using a second query having at least a portion of the first query, at least a portion of the first results, and at least a portion of the set of categories. The method and system can also include scoring the set of second results based upon a relationship of the first query, the second query, and the set of second results.

Abstract: Some embodiments include a method of facilitating item selection based on features. Other embodiments of related systems and methods are also disclosed.

Abstract: Some embodiments include a method of identifying desirable items in a category of items based on features. Other embodiments of related systems and methods are also disclosed.