Abstract: Approaches are described for ranking multiple products or other items, such as products obtained in response to a search request submitted to a server. The ranking system determines a ranking score for the products based on both data available online and item data that must be computed offline due to longer computation time or unavailability of data. The ranking score can be used to rank the products and determine which products are the most relevant to the user. A hybrid boosting method is used to first train an online ranking function to produce an online ranking score for the item. In the second phase, an offline ranking function is trained to produce a second ranking score for the item. The online rank score is combined with the offline rank score at query time to produce a combined rank for the items in the search results.

Abstract: The relevance or ranking of various dynamically-determined instances of content can be adjusted or otherwise improved based on aspects such as the freshness or seasonality of the content. In many conventional relevance or ranking algorithms, factors such as popularity, performance, and profit are used to determine which content to present to a user, as well as how to display the selected content. Such algorithms do not necessarily reflect domain-specific knowledge very well, and thus fail to accurately select content that is of differing levels appeal at various ages of the content and/or during various seasons of the year. Freshness and/or seasonality adjustment scores can be used to generate improved relevance, selection, or ranking determinations for various categories of content.

Abstract: The relevance or ranking of various dynamically-determined instances of content can be adjusted or otherwise improved based on aspects such as the freshness or seasonality of the content. In many conventional relevance or ranking algorithms, factors such as popularity, performance, and profit are used to determine which content to present to a user, as well as how to display the selected content. Such algorithms do not necessarily reflect domain-specific knowledge very well, and thus fail to accurately select content that is of differing levels appeal at various ages of the content and/or during various seasons of the year. Freshness and/or seasonality adjustment scores can be used to generate improved relevance, selection, or ranking determinations for various categories of content.

Abstract: Approaches are described for ranking multiple products or other items, such as products obtained in response to a search request submitted to a server. The ranking system determines a ranking score for the products based on both data available online and item data that must be computed offline due to longer computation time or unavailability of data. The ranking score can be used to rank the products and determine which products are the most relevant to the user. A hybrid boosting method is used to first train an online ranking function to produce an online ranking score for the item. In the second phase, an offline ranking function is trained to produce a second ranking score for the item. The online rank score is combined with the offline rank score at query time to produce a combined rank for the items in the search results.

Abstract: Methods and apparatus provide the capability of receiving at least a portion of a message in natural language format from a user prior to submission of the message to an automated agent for a response, analyzing the at least the portion of the message, and providing a suggestion to the user, based upon the analyzed at least the portion of the message, for altering the message to improve ability of the automated agent to respond to the message.

Abstract: The invention is a method for estimating the internal state of a system for the electrochemical storage of electrical energy, such as a battery. For various internal states of batteries of the same type as a battery being analysed, impedance measurements are carried out by adding an electrical signal to the current passing through the batteries. Then, an RC circuit is used to model the impedances. Next, a relationship is calibrated between the SoC (and/or the SoH) and the parameters of the RC circuit using multivariate statistical analysis. A measurement of the impedance of the battery under analysis is carried out which is modeled using the RC circuit. Finally, the relationship of the equivalent electric circuit defined for the battery being analysed is used to estimate the internal state of that battery.

Abstract: The method for selecting a base station for handover from a plurality of target base stations includes receiving, at a network element, measurement reports and loads of the plurality of target base stations, where the plurality of target base stations are within a coverage area of a mobile station. The method further includes selecting, at the network element, the base station from the plurality of target base stations for handover of the mobile station of a source base station to the selected target base station based on the measurement reports and the loads of the plurality of target base stations.

Abstract: A search facility may optimize search result ranking by applying inverted decay transformations to history-dependent ranking components. Ranking scores for content in a content collection may be based on a set of ranking components including history-dependent ranking components. History-dependent ranking components may be based on historical behavioral data such as historical searches, actions taken with respect to content such as viewing content and content-related purchases. Content recently added to the content collection may be disadvantaged relative to content with an established history. Inverted decay transformations may correspond to simulations of additional historical behavioral data.

Abstract: A system and method are provided for escalating a user or customer to a live agent from a conversational agent when predetermined criteria are met. The conversational agent textually converses in so-called natural language interaction and can run on a computer, such as a server. Upon receiving a first query, the conversational agent creates a new case, and interacts with the customer, in an attempt to resolve the case and satisfy the user. The predetermined criteria for escalation may include a determination that the conversational agent is unable to satisfy a computer-to-computer information request. Alternatively, the predetermined criteria may include patterns and/or words associated with frustration, for example, and/or unrecognized query subject matter, high priority queries, for example to increase sales, etc.

Abstract: A system and method are provided for escalating a user or customer to a live agent from a conversational agent when predetermined criteria are met. The conversational agent textually converses in so-called natural language interaction and can run on a computer, such as a server. Upon receiving a first query, the conversational agent creates a new case, and interacts with the customer, in an attempt to resolve the case and satisfy the user. The predetermined criteria for escalation may include a determination that the conversational agent is unable to satisfy a computer-to-computer information request. Alternatively, the predetermined criteria may include patterns and/or words associated with frustration, for example, and/or unrecognized query subject matter, high priority queries, for example to increase sales, etc.

Abstract: A conversational agent receives a textual user message and escalates the user to a live agent if predetermined criteria are met.

Abstract: The method for selecting a base station for handover from a plurality of target base stations includes receiving, at a network element, measurement reports and loads of the plurality of target base stations, where the plurality of target base stations are within a coverage area of a mobile station. The method further includes selecting, at the network element, the base station from the plurality of target base stations for handover of the mobile station of a source base station to the selected target base station based on the measurement reports and the loads of the plurality of target base stations.

Abstract: Methods and apparatus to evaluate the semantic proximity between reference free-form text entry and a candidate free-form text request.

Abstract: Methods and apparatus to evaluate the semantic proximity between reference free-form text entry and a candidate free-form text request.

Abstract: Methods and apparatus to evaluate the semantic proximity between reference free-form text entry and a candidate free-form text request.

Abstract: Methods and apparatus provide the capability of receiving at least a portion of a message in natural language format from a user prior to submission of the message to an automated agent for a response, analyzing the at least the portion of the message, and providing a suggestion to the user, based upon the analyzed at least the portion of the message, for altering the message to improve ability of the automated agent to respond to the message.

Abstract: Methods and apparatus to enable a search engine to receive natural language queries and provide answers to user queries. The answer can be extracted from the search results. In one embodiment, the answer can be highlighted.

Abstract: Methods and apparatus to evaluate the semantic proximity between reference free-form text entry and a candidate free-form text request.

Abstract: A conversational agent receives a textual user message and escalates the user to a live agent if predetermined criteria are met.