Using Machine Learning to Predict Outcomes for Documents

A method, comprising:

• receiving an electronic document from a user interface generated on a client device via a computer network, the electronic document having content directed toward achieving an objective, and the user interface configured to allow a user of the client device to edit the electronic document;
• extracting a set of features from the content of the electronic document, the extracted features including at least a set of phrase-related features for a set of distinctive phrases present in the content of the electronic document and categories corresponding to the set of distinctive phrases;
• evaluating the set of features extracted from the content of the electronic document and the objective to which the content of the document is directed toward to predict an outcome of the electronic document with respect to the objective, evaluating the set of features comprising:
• assigning weights to each features in the set of features, and combining the weights of the set of features to generate the predicted outcome of the electronic document;
• and
• presenting evaluation results for display on the user interface of the client device, wherein presenting the evaluation results comprises:
• providing the predicted outcome for display at a region of the user interface adjacent to the electronic document,
• for each distinctive phrase in the set of distinctive phrases, highlighting the distinctive phrase in the content of the electronic document within the user interface to generate a phrase highlight for the distinctive phrase, wherein the phrase highlight is generated to graphically distinguish the category associated with the distinctive phrase, and
• displaying at least one phrase-related feature for at least one distinctive phrase adjacent to the content of the electronic document.

A non-transitory computer-readable storage medium comprising stored instructions executable by a processor system, the instructions when executed causing the processor system to:

• receive an electronic document from a user interface generated on a client device via a computer network, the electronic document having content directed toward achieving an objective, and the user interface configured to allow a user of the client device to edit the electronic document;
• extract a set of features from the content of the electronic document, the extracted features including at least a set of phrase-related features for a set of distinctive phrases present in the content of the electronic document and categories corresponding to the set of distinctive phrases;
• evaluate the set of features extracted from the content of the electronic document and the objective to which the content of the document is directed toward to predict an outcome of the electronic document with respect to the objective, wherein the instructions further cause the processor system to:
• assign weights to each features in the set of features, and
• combine the weights of the set of features to generate the predicted outcome of the electronic document;
• and
• present evaluation results for display on the user interface of the client device, wherein the instructions further cause the processor system to:
• provide the predicted outcome for display at a region of the user interface adjacent to the electronic document,
• for each distinctive phrase in the set of distinctive phrases, highlight the distinctive phrase in the content of the electronic document within the user interface to generate a phrase highlight for the distinctive phrase, wherein the phrase highlight is generated to graphically distinguish the category associated with the distinctive phrase, and
• display at least one phrase-related feature for at least one distinctive phrase adjacent to the content of the electronic document.