Abstract: The present disclosure relates to systems, non-transitory computer readable media, and methods for detecting and providing a digital notification of whether a ridership error exists. For instance, a ridership error detection system identifies a transportation match between a requestor device and a provider device. The ridership error detection system determines one or more sets of provider-requestor consistency signals from the requestor device and the provider device across ride stages. For instance, the ridership error detection system analyzes location signals, IMU signals, audio signals, local wireless signals indicating distances between the requestor device and the provider device, and other signals to determine whether a ridership error exists. The ridership error detection system provides digital notifications to the provider device and the requestor device based on the ridership error determination.

Abstract: The present disclosure relates to systems, non-transitory computer readable media, and methods for detecting and providing a digital notification of whether a ridership error exists. For instance, a ridership error detection system identifies a transportation match between a requestor device and a provider device. The ridership error detection system determines one or more sets of provider-requestor consistency signals from the requestor device and the provider device across ride stages. For instance, the ridership error detection system analyzes location signals, IMU signals, audio signals, local wireless signals indicating distances between the requestor device and the provider device, and other signals to determine whether a ridership error exists. The ridership error detection system provides digital notifications to the provider device and the requestor device based on the ridership error determination.

Abstract: The present disclosure relates to systems, non-transitory computer readable media, and methods for detecting and providing a digital notification of whether a ridership error exists. For instance, a ridership error detection system identifies a transportation match between a requestor device and a provider device. The ridership error detection system determines one or more sets of provider-requestor consistency signals from the requestor device and the provider device across ride stages. For instance, the ridership error detection system analyzes location signals, IMU signals, audio signals, local wireless signals indicating distances between the requestor device and the provider device, and other signals to determine whether a ridership error exists. The ridership error detection system provides digital notifications to the provider device and the requestor device based on the ridership error determination.

Abstract: A computer-implemented method of automatically organizing email messages is performed at a computer system. In the method, a plurality of email messages is accessed. A set of email addresses included in the email messages is identified, respective weights are assigned to respective email addresses in the set of email addresses, and the plurality of email messages is divided into clusters in accordance with the respective weights. Email messages of the plurality of email messages are provided for display, organized by the respective clusters.

Abstract: A method for determining quality signals for offer campaigns comprises an offer system that receives information submitted by users, and analyzes it to learn features of each user and detect patterns. The offer system clusters the users, and transmits an offer to a limited number of users in each user cluster. It receives notification that a user interacted with the offer and determines a conversion rate for each cluster. If the conversion rate exceeds a pre-defined threshold, the offer system transmits the offer to the remaining users in the cluster. Alternatively, the features of the users are rendered into a multi-dimensional graph that plots the distribution of the users. The offer system marks a representation of each user that interacts with the offer on the graph to determine groupings of users. The offer system transmits the offer to the remaining users in each group.

Abstract: A method for determining quality signals for offer campaigns comprises an offer system that receives information submitted by users, and analyzes it to learn features of each user and detect patterns. The offer system clusters the users, and transmits an offer to a limited number of users in each user cluster. It receives notification that a user interacted with the offer and determines a conversion rate for each cluster. If the conversion rate exceeds a pre-defined threshold, the offer system transmits the offer to the remaining users in the cluster. Alternatively, the features of the users are rendered into a multi-dimensional graph that plots the distribution of the users. The offer system marks a representation of each user that interacts with the offer on the graph to determine groupings of users. The offer system transmits the offer to the remaining users in each group.

Abstract: In an automatic electronic discovery search tool, documents can be clustered into a cluster hierarchy according to a first clustering approach. Once a hierarchy tree is created, portions of the tree can be flattened for application of a second superior clustering approach. Clustered portions may be used in a document review tool or further filtered according to specified criteria. Clusters may be filtered or used in a document review tool.

Abstract: In an automatic electronic discovery search tool, documents can be clustered into a cluster hierarchy using data contained in a first field of the documents. One of more levels of the cluster hierarchy are merged. Merged clusters are further clustered using data contained in a second field of the documents. The first field and second field may be determined by the signal-to-noise ratio of the data contained in the fields. Clusters may be filtered or used in a document review tool.

Abstract: A computer-implemented method of automatically organizing email messages is performed at a computer system. In the method, a plurality of email messages is accessed. A set of email addresses included in the email messages is identified, respective weights are assigned to respective email addresses in the set of email addresses, and the plurality of email messages is divided into clusters in accordance with the respective weights. Email messages of the plurality of email messages are provided for display, organized by the respective clusters.

Abstract: In an automatic electronic discovery search tool, emails subject to a litigation hold can be clustered using collaborative information rather than the contents to speed the review process. Collaborative information may include non-content fields such as the sender or recipient of a document or message. Documents may then be reviewed as a group based on the collaborative information, or further filtered in accordance with desired criteria.