Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. Relating and correlating this data at and across various levels help in obtaining a perspective about the educational institution. A structural representation captures the essence of all of the relationships in a unified manner and an important aspect of the relationship is the so-called “influence factor.” This factor indicates influencing effect of an entity over another entity, wherein the entities are a part of the structural representation. Given such a structural representation, a system and method that propagates the influence factors of the entities to arrive at a stable representation from the point of view of influences is discussed.

Abstract: An educational institution (also referred as a university) is structurally modeled using a university model graph. A key benefit of modeling of the educational institution is to help in an introspective analysis by the educational institute. Specifically, the model is quite beneficial for undertaking the analysis of the various issues faced by the educational institute. A what-if scenario requires the model to be suitably changed to address the issue under consideration and the changed model needs to be analyzed to determine how the issue could be handled. A system and method for what-if scenario analysis based on the university model graph is discussed.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. Relating and correlating this data at and across various levels help in obtaining a perspective about the educational institution. A structural representation captures the essence of all of the relationships in a unified manner and an important aspect of the relationship is the so-called “influence factor.” This factor indicates influencing effect of an entity over another entity, wherein the entities are a part of the structural representation. A system and method for the construction of such a structural representation of an educational institution based on the educational institution specific information is discussed.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. A structural representation that captures the essence of all of the relationships in a unified manner has concise information about the educational institution, and visualization is a way to bring out all this information in an explicit manner so that the various of the users of the educational institution system understand effectively their system. A system and method for visualization based on the structural representation of a university along a variety of dimensions is discussed.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. Relating and correlating this data at and across various levels help in obtaining a perspective about the educational institution. A structural representation captures the essence of all of the relationships in a unified manner and an important aspect of the relationship is the so-called “influence factor.” This factor indicates influencing effect of an entity over another entity, wherein the entities are a part of the structural representation. Given such a structural representation, a system and method that propagates the influence factors of the entities to arrive at a stable representation from the point of view of influences is discussed.

Abstract: An educational institution (also referred as a university) is structurally modeled using a university model graph. Such a model helps compare educational institutions at various levels—university level, department level, faculty member level, or student level. One of the requirements of comparison is to normalize the similarities and identify and elaborate the differences across multiple educational institutions. A way to achieve this is to model the educational institutions using comparable elements; specifically, the university model graph allows for such comparison as multiple educational institutions are modeled based on the same set of concepts and notions. A system and method for comparing educational institutions based on their respective university model graphs is discussed.

Abstract: Personalized services and targeted services demand the exploitation of context—say, context of an environment, context of a product, context of a service, and context of a customer or user or individual. In order for the personalized and targeted services to have a greater impact, the identified context used by a context aware processing engine needs to be accurate and current. Such an up-to-date context is called as context map and a system and method for generating a customer-specific context map involves the processing of customer transactions, abstracting and generalizing these transactions into entities, and inter-relating these entities. The context map, for example, is useful in ad targeting in mobile environments, and in quicker and efficient problem resolution in contact center environments.

Abstract: Peer to peer interactions are a popular way of social networking. Such peer to peer interactions play an important role in (a) obtaining relevant and latest information; (b) obtaining relevant experiential information; (c) obtaining of relevant opinions on, say, products; (d) collaborative problem solving, and so on. Consider a scenario of classified ads: a user visiting a portal through a mobile phone to decide on buying of a product can be well assisted by facilitating peer to peer interactions. In many situations, it is required to make the right selection of peers in order to be able to obtain the right information, and furthermore, voice is a preferred mode of interaction if mobile phones are used in peer to peer interactions. Also, in peer to peer interactions, anonymity is important in order to protect the privacy of the peers.

Abstract: An educational institution (also referred as a university) is structurally modeled using a university model graph. Such a model helps compare educational institutions at various levels—university level, department level, faculty member level, or student level. One of the requirements of comparison is to normalize the similarities and identify and elaborate the differences across multiple educational institutions. A way to achieve this is to model the educational institutions using comparable elements; specifically, the university model graph allows for such comparison as multiple educational institutions are modeled based on the same set of concepts and notions. A system and method for comparing educational institutions based on their respective university model graphs is discussed.

Abstract: An educational institution (also referred as a university) is structurally modeled using a university model graph. A key benefit of modeling of the educational institution is to help in an introspective analysis by the educational institute. Specifically, the model is quite beneficial for undertaking the analysis of the various issues faced by the educational institute. A what-if scenario requires the model to be suitably changed to address the issue under consideration and the changed model needs to be analyzed to determine how the issue could be handled. A system and method for what-if scenario analysis based on the university model graph is discussed.

Abstract: Enterprise users access several applications and services routinely to carry out their work-related activities on a day-to-day basis. These applications and services could be hosted within an enterprise or on a third-party data center. The enterprise users login into the applications and services so as to gain access to the applications and services. In the case of single sign-on, it is expected that the users authenticate once to a specific application/service/system and obtain access to any other application/service/system. In such a scenario, it is important to ensure that during the course of this authenticated access grant, the right users are provided access to right information. This is achieved by a re-authentication system that demands minimum re-authentication effort from “right” users and maximum re-authentication effort from “non-right” users. A system and method of on the fly re-authentication involves a novel challenge-response mechanism.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. Relating and correlating this data at and across various levels help in obtaining a perspective about the educational institution. A structural representation captures the essence of all of the relationships in a unified manner and an important aspect of the relationship is the so-called “influence factor.” This factor indicates influencing effect of an entity over another entity, wherein the entities are a part of the structural representation. A system and method for the construction of such a structural representation of an educational institution based on the educational institution specific information is discussed.

Abstract: Real-time delivery of multimedia content puts extreme demand on both computational and network resources. Many a times, the requirement is to handle multiple such delivery requirements and as a consequence, the overall delivery efficiency gets affected. Another dimension of complexity is that (a) the multimedia content to be delivered may not always be highly reliable, and (b) the network may also be not highly reliable. In such a situation, it becomes even more difficult to satisfy the quality of service requirements. When content to be delivered to multiple destinations is available at multiple sources, there is an opportunity to overcome the above mentioned complexity. The system and method for efficient delivery in a multi-source multi-destination network involves pulling of data from the multiple sources by measuring quality of service and reliability parameters, and efficiently loading the systems and the network in a cooperative manner.

Abstract: IP networks carry packets that consist of headers and payloads. Typical traffic analysis systems at layer 3 process packet headers in order to obtain as much information about the traffic as possible. However, performing of deep packet analysis requires the processing of packet payloads as well. Another important requirement of layer 3 processing is the need to process the payloads at wire speeds. A system and method for deep packet inspection at layer 3 involves (a) an approach for packet payload processing; (b) accounting for out of order arrival of packets; (c) an approach for partial match analysis so as to be able to analyze the traffic flows when only partial information is available; and (d) an approach for effective payload processing for attempting to achieve wire speed processing.

Abstract: Annotations for a multimedia repository facilitate an efficient indexing, searching, and retrieval of the content from the multimedia repository. These annotations are an effective description of the content and it is very useful to have systems that automatically analyze the content to generate the annotations. A multimedia content, comprising video, audio, and textual data, is organized at shot level, scene level, segment level, multi-segment level, and full-length level. The multimedia content annotation is a providing of computer processable description of the multimedia content. Due to the multilevel organization of a multimedia content, it is required to provide annotations at various levels as well. A system and method for annotation aggregation uses the annotation at a lower level to arrive at an annotation at the next higher level. Such multilevel annotations are very useful in applications such as targeted content delivery.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. Relating and correlating this data at and across various levels help in obtaining a perspective about the educational institution. A structural representation captures the essence of all of the relationships in a unified manner and an important aspect of the relationship is the so-called “influence factor.” This factor indicates influencing effect of an entity over another entity, wherein the entities are a part of the structural representation. Given such a structural representation, a system and method that propagates the influence factors of the entities to arrive at a stable representation from the point of view of influences is discussed.

Abstract: An educational institution (also referred as a university) is rich with multiple kinds of data: students, faculty members, departments, divisions, and at university level. A structural representation that captures the essence of all of the relationships in a unified manner has concise information about the educational institution, and visualization is a way to bring out all this information in an explicit manner so that the various of the users of the educational institution system understand effectively their system. A system and method for visualization based on the structural representation of a university along a variety of dimensions is discussed.

Abstract: Enterprise users access several applications and services routinely to carry out their work-related activities on a day-to-day basis. These applications and services could be hosted within an enterprise or on a third-party data center. The enterprise users login into the applications and services so as to gain access to the applications and services. In the case of single sign-on, it is expected that the users authenticate once to a specific application/service/system and obtain access to any other application/service/system. In such a scenario, it is important to ensure that during the course of this authenticated access grant, the right users are provided access to right information. This is achieved by a re-authentication system that demands minimum re-authentication effort from “right” users and maximum re-authentication effort from “non-right” users. A system and method of on the fly re-authentication involves a novel challenge-response mechanism.

Abstract: IP networks carry packets that consist of headers and payloads. Typical traffic analysis systems at layer 3 process packet headers in order to obtain as much information about the traffic as possible. However, performing of deep packet analysis requires the processing of packet payloads as well. Another important requirement of layer 3 processing is the need to process the payloads at wire speeds. A system and method for deep packet inspection at layer 3 involves (a) an approach for packet payload processing; (b) accounting for out of order arrival of packets; (c) an approach for partial match analysis so as to be able to analyze the traffic flows when only partial information is available; and (d) an approach for effective payload processing for attempting to achieve wire speed processing.

Abstract: Customers buy a variety of equipments and gadgets from multiple vendors and interact with manufacturers through contact centers to get their questions on the bought products answered. The market opportunities and competitiveness are forcing manufacturers to be accommodative and innovative in providing post-sale support. An essential aspect of this market dynamics is customer churn and the manufactures are required to ensure that product loyalty and brand loyalty of the customers are high. While Customer Relationship Management (CRM) has been playing an all important role of monitoring and managing customer relationships, it is necessary to augment CRM with more specific enhancements. The need is to have an integrated, practical, and realizable approach that focuses on measuring customer satisfaction index based on multiple interactions of customers with manufacturers.