Abstract: A computer receives an electronic document that includes a group of terms. The computer sends the electronic document to an information extraction program that extracts specific terms from the group of terms. Each of the specific terms that match to a certain extent with one of the attribute values in an electronic dictionary is identified. A value associated with the electronic document is generated based on the specific terms that match, and on an end-user that is attempting to access the electronic document.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: A Customer Relationship Management (CRM) offer template is established in data storage and includes at least one variable field and having at least one offer attribute. For each of a plurality of customer groups, a data processing system calculates an expected benefit to be obtained by sending an instantiated CRM offer to a customer based upon historical responses, offer cost, and legal values of the at least one variable field. The data processing system outputs a CRM offer instance and target list of customers that maximizes the expected benefit.

Abstract: Systems and associated methods for automated and semi-automated building of domain models for documents are described. Embodiments provide an approach to discover an information model by mining documentation about a particular domain captured in the documents. Embodiments classify the documents into one or more types corresponding to concepts using indicative words, identify candidate model elements (concepts) for document types, identify relationships both within and across document types, and consolidate and learn a global model for the domain.

Abstract: Analyzing transcripts of conversation between at least two users by receiving input information from a first user via a voice call, creating conversational transcripts from the information received from the first user, selecting at least one defined situation from a list of defined situations, identifying the selected situation in the conversational transcripts, identifying a set of procedural sequences by comparing the at least one identified situation in the conversational transcripts with knowledge derived from a corpus of historical conversational transcripts; and providing the set of procedural sequences to the first user.

Abstract: Embodiments of the invention provide retailers with the ability to employ concept-based marketing using only a few representative examples. Embodiments of the invention take seed examples, utilize the seed examples to provide an expanded list (that can be edited as desired) representative of the concept, and map the expanded list to a final set of customers to be included in a targeted marketing operation.

Abstract: Systems and methods of marketing to mobile devices are provided. Other methods, apparatus, and computer readable media are also provided.

Abstract: Techniques for retrieval of one or more relevant multi-attribute structured objects with respect to a query are provided. The techniques include receiving a query, grouping one or more attributes of one or more objects in a database into one or more groups according to how each bears a relation to the query, and using the one or more attribute groups to produce an output of one or more relevant multi-attribute structured objects in response to the query.

Abstract: Online and other electronic surveys are increasingly being looked upon as highly useful and versatile tools for gauging popular opinions in a variety of areas. Challenges continually arise in terms of optimizing questionnaires so as to maximize their effectiveness in mapping trends among a population over time. There is broadly contemplated herein, in accordance with at least one embodiment, of the invention, the automation of the usage of value dependencies by way of exposing and eliminating redundancy in survey or questionnaire databases. Dynamically, updated information can be used to continuously evolve a selection of questions, while fairness can be ensured in this selection by averting a situation of continual non-selection of certain questions.

Abstract: Techniques for segregating one or more logs of at least one multitasking user to derive at least one behavioral pattern of the at least one multitasking user are provided. The techniques include obtaining at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information, correlating the at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information to determine a task associated with each of one or more actions and segregate the one or more logs based on the one or more actions, and using the one or more logs that have been segregated to derive at least one behavioral pattern of the at least one multitasking user. Techniques are also provided for deriving intelligence from at least one activity log of at least one multitasking user to provide information to the at least one user.

Abstract: Techniques for segregating one or more logs of at least one multitasking user to derive at least one behavioral pattern of the at least one multitasking user are provided. The techniques include obtaining at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information, correlating the at least one of at least one action log, configuration information, domain knowledge, at least one task history and open task repository information to determine a task associated with each of one or more actions and segregate the one or more logs based on the one or more actions, and using the one or more logs that have been segregated to derive at least one behavioral pattern of the at least one multitasking user. Techniques are also provided for deriving intelligence from at least one activity log of at least one multitasking user to provide information to the at least one user.

Abstract: A method is provided for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications that comprises dividing the communication transcripts of the corpus into a first set of sentences spoken by a caller and a second set of sentences spoken by a responder; generating a set of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters with

Abstract: A method is provided for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications that comprises dividing the communication transcripts of the corpus into a first set of sentences spoken by a caller and a second set of sentences spoken by a responder; generating a specified number of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence