Abstract: A method of an attribution server. The method determines publishing channels for advertisements in a marketing campaign to analyze their marketing effectiveness for purchasable items using a processor and a memory of the attribution server. Data points are associated with users. A K-th order attribution model is constructed. Independent and dependent variables of the attribution model are associated with various types of marketing data. An observation matrix and a conversion vector are determined. A regression analysis is performed with refining steps. Insignificant second order cross terms of the attribution model are identified and removed. A modified K-th order attribution model is constructed. Another regression analysis is performed to find optimal model parameters.

Abstract: A system for generating a new dataset gleans a corpus of datasets to find attributes that could be used to construct a new dataset. When an entity selects attributes, the system analyzes relationships between the selected attributes and unselected attributes in order to generate a ranked list of suggested attributes, with the most relevant attributes at the top of the list. The system could also use this system to suggest transformations to the attributes for use in the new dataset. The entity could then select additional attributes and/or transformations to apply to the new dataset before the new dataset is generated.

Abstract: A method of an attribution server. The method determines publishing channels for advertisements in a marketing campaign to analyze their marketing effectiveness for purchasable items using a processor and a memory of the attribution server. Data points are associated with users. A K-th order attribution model is constructed. Independent and dependent variables of the attribution model are associated with various types of marketing data. An observation matrix and a conversion vector are determined. A regression analysis is performed with refining steps. Insignificant second order cross terms of the attribution model are identified and removed. A modified K-th order attribution model is constructed. Another regression analysis is performed to find optimal model parameters.

Abstract: A system for synthesizing new datasets from a corpus of data sources is disclosed. The system analyzes attributes between the different datasets between the data sources to determine if there are possible relationships between the attributes. Where a possible relationship is identified, the system could generate a confidence metric between 0%-100% reflecting how likely it is that the attributes are related. The system could then synthesize a new dataset as a function of the generated confidence metric.

Abstract: A system for generating a new dataset gleans a corpus of datasets to find attributes that could be used to construct a new dataset. When an entity selects attributes, the system analyzes relationships between the selected attributes and unselected attributes in order to generate a ranked list of suggested attributes, with the most relevant attributes at the top of the list. The system could also use this system to suggest transformations to the attributes for use in the new dataset. The entity could then select additional attributes and/or transformations to apply to the new dataset before the new dataset is generated.

Abstract: A system for synthesizing a data shape from a plurality of datasets with a plurality of attributes is provided. As a user entity selects one or more attributes, the system could determine the most relevant attributes and transformations that are related to the selected attributes. As the user selects more attributes and transformations, the data shape could take form with updated rankings, and the system could provide more relevant, targeted suggestions. The data shape could then be used to create a synthesized dataset among the plurality of datasets, and could be saved as a type of query for deriving future datasets.

Abstract: An intermediate device receives a content data message addressed to a receiving device for a communication session between a source device and the receiving device. The intermediate device substitutes adapted content data for content data of the content data message and then sends the adapted content data to the receiving device such that it appears to the receiving device that the adapted content data originated from the source device. The communication from the source device to the receiving device is intercepted by the intermediate device in a manner that is transparent to the source device and receiving device.

Abstract: An intermediate device receives a content data message addressed to a receiving device for a communication session between a source device and the receiving device. The intermediate device substitutes adapted content data for content data of the content data message and then sends the adapted content data to the receiving device such that it appears to the receiving device that the adapted content data originated from the source device. The communication from the source device to the receiving device is intercepted by the intermediate device in a manner that is transparent to the source device and receiving device.

Abstract: Apparatus, methods, and machine-readable articles of manufacture enable a telephone system to distinguish between actual events and echoes. Events may include conferees' voice and DTMF commands. In selected embodiments, the system categorizes an event received on one channel as a real event if the energy of the event's waveform is greater than concurrent energy of every other channel of the same conference. Otherwise, the event is stored. When the system receives a new event of the same type on a channel of the same conference during a predetermined period, it compares the energies of the new and stored events. If the energy of the new event exceeds that of the stored event, the new event becomes the stored event, and the old stored event is ignored. At the end of the period, the stored event is categorized as a real event and forwarded to appropriate application code.

Abstract: Systems, methods, and machine-readable articles of manufacture enable private notification of a participant in a telephone conference. In representative embodiments, a system receives a telephone call intended for a first conference participant, generates an informative announcement containing information regarding the call, mixes the informative announcement with the conference audio, and privately plays the mixed audio to the first participant. In other representative embodiments, the system concurrently generates a non-informative announcement, mixes the non-informative announcement with the conference audio, and plays the second mixed audio to the other conference participant or participants. In this way, the first participant is notified of the incoming call while simultaneously listening to the conference audio, and the information regarding the call is not shared with the other conference participant or participants.

Abstract: A method for identifying end of voiced speech within an audio stream of a noisy environment employs a speech discriminator. The discriminator analyzes each window of the audio stream, producing an output corresponding to the window. The output is used to classify the window in one of several classes, for example, (1) speech, (2) silence, or (3) noise. A state machine processes the window classifications, incrementing counters as each window is classified: speech counter for speech windows, silence counter for silence, and noise counter for noise. If the speech counter indicates a predefined number of windows, the state machine clears all counters. Otherwise, the state machine appropriately weights the values in the silence and noise counters, adds the weighted values, and compares the sum to a limit imposed on the number of non-voice windows. When the non-voice limit is reached, the state machine terminates processing of the audio stream.