Abstract: The disclosed embodiments illustrate methods and systems for summary generation of a real-time conversation. The method includes receiving a real-time conversation from a plurality of computing devices over a communication network. The method further includes determining one or more first features of the real-time conversation between at least a first user and a second user. The method further includes extracting one or more second features from the one or more first features, based on one or more pre-defined criteria. The method further includes generating a summary content of the real-time conversation, based on at least the extracted one or more second features and one or more annotations associated with the determined one or more first features by use of one or more trained classifier. Further, the method includes rendering the generated summary content on a user interface displayed on at least one of the plurality of computing devices.

Abstract: The disclosed embodiments illustrate methods and systems for summary generation of a real-time conversation. The method includes receiving a real-time conversation from a plurality of computing devices over a communication network. The method further includes determining one or more first features of the real-time conversation between at least a first user and a second user. The method further includes extracting one or more second features from the one or more first features, based on one or more pre-defined criteria. The method further includes generating a summary content of the real-time conversation, based on at least the extracted one or more second features and one or more annotations associated with the determined one or more first features by use of one or more trained classifier. Further, the method includes rendering the generated summary content on a user interface displayed on at least one of the plurality of computing devices.

Abstract: The disclosed embodiments illustrate methods data processing for real-time text analysis. The method includes receiving text content from a plurality of user-computing devices, wherein the text content comprises at least a current text segment and a previous text segment. The method further includes extracting one or more first features from the current text segment, wherein at least a first feature of the one or more first features corresponds to a difference between timestamps associated with each of the current text segment and the previous text segment. The method further includes categorizing the current text segment into a predetermined category of one or more predetermined categories, based on at least the one or more first features, automatically by utilizing a classifier. Further, the method includes predicting a likelihood of evolution of an attribute in the text content, based on the predetermined category associated with the current text segment.

Abstract: The disclosed embodiments illustrate methods of data processing for text classification of a target domain. The method includes generating a plurality of clusters from a plurality of first text segments corresponding to a plurality of source domains, based on an association of the plurality of first text segments with a plurality of categories. The method further includes computing a similarity score of each of a plurality of second text segments corresponding to the target domain for each of the plurality of clusters. The method further includes identifying a pre-specified count of clusters from the plurality of clusters, based on the computed similarity score. Further, the method includes training a first classifier by utilizing first text segments in the identified pre-specified count of clusters, wherein the trained first classifier is utilized to automatically classify the plurality of second text segments into categories associated with the identified pre-specified count of clusters.

Abstract: The disclosed embodiments illustrate methods for voice-based user authentication and content evaluation. The method includes receiving a voice input of a user from a user-computing device, wherein the voice input corresponds to a response to a query. The method further includes authenticating the user based on a comparison of a voiceprint of the voice input and a sample voiceprint of the user. Further, the method includes evaluating content of the response of the user based on the authentication and a comparison between text content and a set of pre-defined answers to the query, wherein the text content is determined based on the received voice input.

Abstract: A system for identifying a root-cause of customer churn for churn prediction refinement. Customer transactions are analyzed to identify discriminating patterns that appear frequently in the transactions of customers who have churned and infrequent in the transactions of customers who have not churned. Attributes associated with the discriminating patters are the root-causes of customer churn. The attributes of customer transactions associated with the root-causes of customer churn are weighted. Churn prediction is performed on the updated customer transactions to obtain a second list of customers likely to churn. The first and second lists are compared to determine whether convergence has occurred. Upon convergence, the second list of customers likely to churn to a display device of a customer care agent so that those customers on the second list can be prioritized ahead of customers who are not likely to churn. Otherwise, the process repeats until convergence.

Abstract: The present disclosure provides a method for incenting potential contributors for creating content in response to a posting. The method comprises: posting a task to a first crowdsource with the task having a first expiry period of ?1; waiting for ?1 period to expire; determining whether the task is complete; reposting the task if not complete including a second expiry period of ?2; waiting for the second period of ?2 to expire; reposting the task if not yet complete including an increased reward and a third expiry period of ?3; waiting for the third period of ?3 to expire; and, reposting the task if still not complete, wherein the reposting includes a second crowdsource.

Abstract: The disclosed embodiments illustrate a method and a system for predicting future activities of a user on a social media platform. The method includes extracting a first time series of one or more historical activities performed by the user from a social media platform server. The method further includes receiving a second time series of one or more future events from a requestor-computing device. The method further includes determining a first set of forecast values and a second set of forecast values based on the first time series and/or the second time series, wherein the first set of forecast values is determined using an ARIMA technique, and the second set of forecast values is determined using a regression modelling technique. The method further includes predicting the future activities of the user based on the first set of forecast values and the second set of forecast values.

Abstract: The disclosed embodiments illustrate methods and systems for creating one or more tasks of digitizing an electronic document. The electronic document comprises one or more fields. The method comprising receiving inputs to define one or more characteristics associated with each of the one or more fields. The one or more fields are categorized in one or more groups based on the one or more characteristics. Additionally, a task is created for each of the one or more categorized fields based on the one or more characteristics associated with each of the one or more categorized fields, wherein the task comprises at least a user interface for facilitating at least one remote worker to input a response for the task.

Abstract: A method, non-transitory computer readable medium and apparatus for transforming a knowledge base into a machine readable format for an automated system are disclosed. For example, the method includes clustering two or more documents of a plurality of documents in the knowledge base that are similar based upon a domain specific shingling function, identifying a pattern from each document of the plurality of documents that are clustered, wherein the pattern comprises a sequence of steps, aggregating the pattern of the each document of the plurality of documents that are clustered into a trie data-structure that is machine readable, receiving a request and applying the trie data-structure to provide a solution to the request.

Abstract: Methods and systems for training a conversation-classification model are disclosed. A first set of conversations in a source domain and a second set of conversation in a target domain are received. Each of the first set of conversations has an associated predetermined tag. One or more features are extracted from the first set of conversations and from the second set of conversations. Based on the similarity of content in the first set of conversations and the second set of conversations, a first weight is assigned to each conversation of the first set of conversations. Further, a second weight is assigned to the one or more features of the first set of conversations based on the similarity of the one or more features of the first set of conversations and of the second set of conversations. A conversation-classification model is trained based on the first weight and the second weight.

Abstract: The disclosed embodiments illustrate methods and systems for predicting requirements of a user for resources. The method includes transforming a message posted by the user into a first message vector. The method further includes categorizing one or more first message vectors into one or more categories. The method further includes transforming each of the categorized first message vectors into one or more second message vectors using a wavelet transform technique. The method further includes determining, for each of the categorized first message vectors, a first score based on at least a probability distribution of one or more coefficients associated with each associated feature. The method further includes selecting a predefined number of features based on at least the first score. The method further includes training one or more classifiers on the selected predefined number of features to identify at least the one or more needs of the user.

Abstract: The disclosed embodiments relates to a crowdsourcing directory system. The crowdsourcing directory system is configured for identifying and comparing one or more of a plurality of crowdsourcing platforms based on a plurality of attributes associated with each of the plurality of crowdsourcing platforms. The crowdsourcing directory system then recommends a set of crowdsourcing platforms from the one or more crowdsourcing platforms based on values of the plurality of attributes. The crowdsourcing directory system also maintains a repository of information pertaining to the plurality of crowdsourcing platforms. In an embodiment, the repository may be updated by implementing software adaptors configured to extract various information pertaining to the plurality of crowdsourcing platforms.

Abstract: The disclosed embodiments illustrate methods and systems for managing a conversation between a first user and a customer care agent. The method includes extracting one or more features from a first conversation between said first user and said customer care agent. The first conversation corresponds to an ongoing conversation over an electronic communication medium. The method includes determining a score for a feature. The score indicates a deviation of a value of said feature from an average of values of said feature determined from historical conversations involving said first user. The method includes aggregating said score for each of said one or more features of said first conversation. Thereafter, the method includes redirecting said first conversation of said first user to a third user during said first conversation based on said aggregation. The third user manages said first conversation between said first user and said customer care agent.

Abstract: According to embodiments illustrated herein, there is provided a system for predicting a health condition of a first patient. The system includes a document processor configured to extract one or more headings from one or more medical records of the first patient based on one or more predefined rules. The document processor is further configured to extract one or more words from one or more phrases written under each of the extracted one or more headings, wherein the one or more phrases correspond to documentation of the observation of the first patient by a medical attender. The system further includes one or more processors configured to predict the health condition of the first patient based on a count of the one or more words in historical medical records and the one or more medical records.

Abstract: An adaptation method includes using a first classifier trained on projected representations of labeled objects from a first domain to predict pseudo-labels for unlabeled objects in a second domain, based on their projected representations. A classifier ensemble is iteratively learned. The ensemble includes a weighted combination of the first classifier and a second classifier. This includes training the second classifier on the original representations of the unlabeled objects for which a confidence for respective pseudo-labels exceeds a threshold. A classifier ensemble is constructed as a weighted combination of the first classifier and the second classifier. Pseudo-labels are predicted for the remaining original representations of the unlabeled objects with the classifier ensemble and weights of the first and second classifiers in the classifier ensemble are adjusted. As the iterations proceed, the unlabeled objects progressively receive pseudo-labels which can be used for retraining the second classifier.

Abstract: The disclosed embodiments illustrate methods and systems for identifying one or more target users, of a first content, from a social network. The disclosed method includes generating a graph comprising one or more nodes, representative of one or more users of the social network, and one or more edges connecting the one or more nodes. Thereafter, a first set of nodes is selected from the one or more nodes based on at least a first score and/or a second score. Finally, a third set of nodes is selected from the first set of nodes based on at least a polarity score associated with a second set of nodes, determined based on at least a first weight and a second weight, connected to each node in the first set of nodes, wherein the third set of nodes represents the one or more target users.

Abstract: A method, a system, and a computer program product for translating a document are disclosed. A document in a source language is received and text snippets are extracted from the same. The text snippets are sent to a first set of remote workers for translation and a second set of remote workers for validation. The words in the validated text snippets are assigned a probability score. The words with the highest probability score are combined to generate the translated document.

Abstract: Methods and systems for facilitating evaluation of one or more electronic documents. One or more templates are extracted from the one or more electronic documents. At least one area in the one or more templates is identified. The at least one area includes a response provided by a user associated with the electronic document. One or more groups are generated based on similarity between the responses in the at least one area in the one or more templates. The one or more groups are distributed to one or more remote workers or a crowdsourcing platform for the evaluation.

Abstract: A method and system for recommending suitability of crowdsourcing a business process is provided. The method includes generating a plurality of business requirements pertaining to the business processes, and receiving one or more attributes pertaining to one or more sets of crowdsourced workforce. The method further includes generating at least one of a comparison matrix or an optimization function based on the plurality of business requirements and the one or more attributes pertaining to one or more sets of crowdsourced workforce. Lastly, the method provides a recommendation on the suitability of crowdsourcing the business process based on at least one of the comparison matrix or the optimization function.