Abstract: A search system that receives and returns results for split stays is described. The search system receives, from a searching end-user, a listing request specifying a multiple-day length of stay parameter. The search system determines that the multiple-day length of stay parameter of the listing request transgresses a minimum length of stay threshold and, in response, generates a combined listing that includes a first listing of the plurality of listings associated with a first portion of the multiple-day length of stay parameter and a second listing of the plurality of listings associated with a second portion of the multiple-day length of stay parameter. The combined listing is presented with one or more other listings of the plurality of listings that match the listing request in a ranked order.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods transform user search keywords into equivalent keyword formats commonly used and/or found within messaging platforms, and compile a data set from such information from which a search for content can be based. The present disclosure, therefore, provides systems and methods that augment users' search terms with terms found in users' mailboxes for purposes of searching for, identifying and communicating content that is relevant to those users.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods transform user search keywords into equivalent keyword formats commonly used and/or found within messaging platforms, and compile a data set from such information from which a search for content can be based. The present disclosure, therefore, provides systems and methods that augment users' search terms with terms found in users' mailboxes for purposes of searching for, identifying and communicating content that is relevant to those users.

Abstract: The present teaching relates to joint representation of information. In one example, first and second pieces of information are received. Each of the first and second pieces of information relates to one word in a plurality of documents, one of the documents, or one of user to which the documents are given. A model for estimating feature vectors is obtained. The model includes a first neural network model based on a first order of words within one of the documents and a second neural network model based on a second order in which at least some of the documents are given. Based on the model, a first feature vector of the first piece of information and a second feature vector of the second piece of information are estimated. A similarity between the first and second pieces of information is determined based on a distance between the first and second feature vectors.

Abstract: Systems and methods for rewriting query terms are disclosed. The system collects queries and query session data and separates the queries into sequences of queries having common sessions. The sequences of queries are then input into a deep learning network to build a multidimensional word vector in which related terms are nearer one another than unrelated terms. An input query is then received and the system matches the input query in the multidimensional word vector and rewrites the query using the nearest neighbors to the term of the input query.

Abstract: Electronic messages may comprise pieces of economic data, such as an email comprising a first sales receipt and an instant message comprising a second sales receipt. Pieces of economic data may be extracted from electronic messages to obtain a set of extracted economic data. A scale factor may be determined based upon historical economic data (e.g., gross domestic sales data, stock data, etc.). A real-time economic indicator (e.g., a coincident indicator, a leading indicator, etc.) may be determined based upon the set of extracted economic data and the scale factor. The real-time economic indicator may be provided to users, such as through a real-time feedback (e.g., according to a license agreement).

Abstract: Systems and methods for recommending bidded terms are disclosed. The system collects a plurality of bidded terms and separates them into ad groups. The add groups are then combined into sequences of terms, which are fed into a deep learning network to build a multidimensional word vector in which related terms are nearer one another than unrelated terms. An input term is then received and the system matches the input term in the multidimensional word vector and recommends the nearest neighbors to the term.

Abstract: A system stored in a non-transitory medium executable by processor circuitry is provided for generating retargeting keywords based on distributed query word representations. The system includes one or more system databases storing historical web search data. Search retargeting circuitry receives requests to generate sets of retargeting keywords related to one or more categories of an advertisement campaign and pre-processing circuitry retrieves a set of historical web search data related to the one or more categories of the advertisement campaign. Modeling circuitry further applies one or more computational linguistic models to the retrieved set of historical web search data and generates distributed query word representations from the retrieved set of historical web search data. Keyword generator circuitry generates a list of retargeting keywords related to the one or more categories of the advertisement campaign using the generated distributed query word representations.

Abstract: A system and method for generating an occupancy model are disclosed. The model is learned using occupancy data for zones, each zone including cells, which are occupied or not at a given time, each with a sensor, which may be reporting or not. The data provides an observed occupancy corresponding to a number of cells in the respective zone which have reporting sensors, and the number of those sensors which are reporting that the respective cell is occupied. The occupancy model is based on a demand model and a sensor noise model which accounts for behavior of the non-reporting sensors. The noise model assumes that the probability of a sensor being in the reporting state is dependent on whether the respective cell is occupied or not. The model can fit the occupancy data better than one which assumes that non-reporting cells are occupied with the same frequency as reporting ones.

Abstract: Methods and apparatuses for delivering advertisements with electronic content provided over a network and, more specifically, to techniques for selecting among advertisements that are competing for a slot associated with electronic content that is to be delivered over a network, are presented herein. Selecting among advertisements that are competing for a slot is based, at least in part, on an estimated latency for each advertisement. The estimated latency of an advertisement is a prediction of what latency will be experienced if the advertisement is served. The estimated latency may be used as one of the parameters for determining which competing advertisement to place in a slot, where advertisements that are associated with low estimated latencies are favored. For example, if all other parameters are equal, a selection mechanism selects advertisement X over advertisement Y, if the estimated latency for advertisement X is less than the estimated latency of advertisement Y.

Abstract: Embodiments of the invention comprise a computer system and a method for recommending a driving route that reduces parking search time and parking costs. The system is configured to receive information about a current location of a car, a desired destination, and parking preferences, to process this information together with available traffic and parking information in order to calculate a recommended route a car should follow during a parking search, and to communicate the recommended route to the car driver. The driver is instructed to park at the first available spot along selected portions of the recommended route.

Abstract: A system and method for generating an occupancy model are disclosed. The model is learned using occupancy data for zones, each zone including cells, which are occupied or not at a given time, each with a sensor, which may be reporting or not. The data provides an observed occupancy corresponding to a number of cells in the respective zone which have reporting sensors, and the number of those sensors which are reporting that the respective cell is occupied. The occupancy model is based on a demand model and a sensor noise model which accounts for behavior of the non-reporting sensors. The noise model assumes that the probability of a sensor being in the reporting state is dependent on whether the respective cell is occupied or not. The model can fit the occupancy data better than one which assumes that non-reporting cells are occupied with the same frequency as reporting ones.