A computer-implemented method for resolving date ambiguities in electronic communication documents includes identifying, within the documents, date field values each associated with a different instance of a communication segment. The method also includes resolving a candidate date for each different communication segment instance, with each candidate date being associated with a respective priority level indicative of a level of certainty with which the candidate date was resolved, and determining a final date from among the candidate dates at least by comparing the respective priority levels. The method further includes determining, based on the final date, an ordered relationship between the electronic communication documents, and storing metadata indicating the ordered relationship between the electronic communication documents.

A computer-implemented method for resolving date ambiguities in electronic communication documents includes identifying, within the documents, date field values each associated with a different instance of a communication segment. The method also includes resolving a candidate date for each different communication segment instance, with each candidate date being associated with a respective priority level indicative of a level of certainty with which the candidate date was resolved, and determining a final date from among the candidate dates at least by comparing the respective priority levels. The method further includes determining, based on the final date, an ordered relationship between the electronic communication documents, and storing metadata indicating the ordered relationship between the electronic communication documents.

Generating unique document identifiers from content within a selected page region is disclosed. A selection of a first region within a first page of the documents is received from a user, and is defined by a set of first boundaries relative to the first page. A text string of a first base selection page content within the first region is retrieved from the first page. Then the retrieved text string is assigned to a page location index associated with the first page. A text string of a first replicated selection page content is retrieved from a second page. The first replicated selection page content is included in the same first region defined by the set of first boundaries relative to the second page. The retrieved text string of the first replicated selection page content is assigned to a page location index of the second page.

Generating unique document identifiers from content within a selected page region is disclosed. A selection of a first region within a first page of the documents is received from a user, and is defined by a set of first boundaries relative to the first page. A text string of a first base selection page content within the first region is retrieved from the first page. Then the retrieved text string is assigned to a page location index associated with the first page. A text string of a first replicated selection page content is retrieved from a second page. The first replicated selection page content is included in the same first region defined by the set of first boundaries relative to the second page. The retrieved text string of the first replicated selection page content is assigned to a page location index of the second page.

Recommendation and approval of a header for a message includes generating a proposed header based on the name and/or brand of the entity and product and/or content of the message, classifying the proposed header using a machine learning model trained based on historical complaints on previously used headers related to the entity name and brand and product and/or content of the message and recommending the proposed header based on the classification. The training of the machine learning model may include learning a threshold wherein headers having a classification greater than the threshold are not recommended as having a high probability of being wrongly associated with the requesting entity and headers having a classification lower than the threshold are recommended as having a high probability of not being wrongly associated with the requesting entity.

Recommendation and approval of a header for a message includes generating a proposed header based on the name and/or brand of the entity and product and/or content of the message, classifying the proposed header using a machine learning model trained based on historical complaints on previously used headers related to the entity name and brand and product and/or content of the message and recommending the proposed header based on the classification. The training of the machine learning model may include learning a threshold wherein headers having a classification greater than the threshold are not recommended as having a high probability of being wrongly associated with the requesting entity and headers having a classification lower than the threshold are recommended as having a high probability of not being wrongly associated with the requesting entity.

In various embodiments, a meeting narration application generates visualizations of recorded meeting data. The meeting narration application generates a first visualization of a set of parameters based on a set of transcript sentences associated with the recorded meeting data. The meeting narration application displays the first visualization and a first expanded content visualization of a first transcript sentence included in the set of transcript sentences within a graphical user interface (GUI). Subsequently, the meeting narration application receives a user event associated with the first visualization via the GUI. The meeting narration application modifies a first parameter selection associated with the set of parameters based on the user event to generate a modified parameter selection. Based on the modified parameter selection, the meeting narration application displays a first compressed content visualization of the first transcript sentence within the GUI.

An information processing apparatus includes a processor configured to select a teaching material related to a lesson from an answer to a questionnaire of the lesson in which the answer is written, and create a report associated with the selected teaching material.

An information processing apparatus includes a processor configured to select a teaching material related to a lesson from an answer to a questionnaire of the lesson in which the answer is written, and create a report associated with the selected teaching material.

A system for verifying transactions includes a computing server configured to identify an unverified transaction among real-time transactions that the computing server processes on behalf of an organization client. The computing server receives a forward of a documentation record from an end user through a communication channel (e.g., receiving an image of a paper receipt of a transaction without prompting the end user to provide the receipt). The computing server parses the documentation record to extract information (e.g., a transaction date) to verify the unverified transaction. If the information from the parsed documentation record matches corresponding fields of the unverified transaction, the computing server may display a user interface indicating that the transaction was verified.