The vast amount of gathered genomic data from Microarray and other high throughput experiments ma... more The vast amount of gathered genomic data from Microarray and other high throughput experiments makes it extremely difficult for the researcher to interpret the data and form conclusions about the functions of the discovered genes. We can make use of extensive biomedical literature databases like Medline to find the functional similarity between genes using various information retrieval and clustering techniques.
Abstract. We propose a semi-supervised method to extract rule sentences from medical abstracts. M... more Abstract. We propose a semi-supervised method to extract rule sentences from medical abstracts. Medical rules are sentences that give interesting and nontrivial relationship between medical entities. Mining such medical rules is important since the rules thus extracted can be used as inputs to an expert system or in many more other ways. The technique we suggest is based on paraphrasing a set of seed sentences and populating a pattern dictionary of paraphrases of rules.
Abstract Extracting complex relationships automatically from unstructured information resources i... more Abstract Extracting complex relationships automatically from unstructured information resources is a challenging problem. It is an important problem in this present age of abundant machine processable information as there is a need to build intelligent knowledge-aware applications for tasks such search, extraction and reasoning. We have used Conditional Random Fields (CRFs) to identify various relationships from biomedical abstracts.
SVM was applied for classifying documents into epidemiology articles on human genes. This databas... more SVM was applied for classifying documents into epidemiology articles on human genes. This database is part of Genomics and Disease Prevention Information System and is maintained by the Center for Disease Control. This database is updated weekly by querying the PubMed, retrieving the articles, pruning them manually based on the title and then reading the rest of articles to classify them into positive set.
Abstract. Knowledge and user generated content is proliferating on the web in scientific publicat... more Abstract. Knowledge and user generated content is proliferating on the web in scientific publications, information portals and online social media. This knowledge explosion has continued to outpace technological innovation in efficient information access technologies. In this paper, we describe the methods and technologies for 'Conversational Search'as an innovative solution to facilitate easier information access and reduce the information overload for users.
Effective encoding of information is one of the keys to qualitative problem solving. Our aim is t... more Effective encoding of information is one of the keys to qualitative problem solving. Our aim is to explore Knowledge representation techniques that capture meaningful word associations occurring in documents. We have developed iReMedI, a TCBR based problem solving system as a prototype to demonstrate our idea. For representation we have used a combination of NLP and graph based techniques which we call as Shallow Syntactic Triples, Dependency Parses and Semantic Word Chains.
Abstract With the advent of open education resources, social networking technologies and new peda... more Abstract With the advent of open education resources, social networking technologies and new pedagogies for online and blended learning, we are in the early stages of a significant disruption in current models of education. The disruption is fueled by a staggering growth in demand. Open Social Learning systems open a new venue for self-motivated learners to access high quality learning materials.
ABSTRACT Cobot is a new intelligent agent platform that connects users through real-time and off-... more ABSTRACT Cobot is a new intelligent agent platform that connects users through real-time and off-line conversations about their health and medical issues. Intelligent web based information agents (conversational/community bots) participate in each conversation providing highly-relevant real-time informational recommendations and connecting people with relevant conversations and other community members.
Abstract We develop an innovative approach to delivering relevant information using a combination... more Abstract We develop an innovative approach to delivering relevant information using a combination of socio-semantic search and filtering approaches. The goal is to facilitate timely and relevant information access through the medium of conversations by mixing past community specific conversational knowledge and web information access to recommend and connect users and information together.
Abstract With an explosion in the proliferation of user-generated content in communities, informa... more Abstract With an explosion in the proliferation of user-generated content in communities, information overload is increasing and quality of readily available online content is deteriorating. There is an increasing need for intelligent systems that make use of implicit user generated knowledge in communities for community engagement. We describe our approach based on modeling user utterances in communities to proactively target the community for exchange of questions and answers.
Abstract. In this paper, we describe a Conversational Interaction framework as an innovative and ... more Abstract. In this paper, we describe a Conversational Interaction framework as an innovative and natural approach to facilitate easier information access by combining web search and recommendations. This framework includes an intelligent information agent (Cobot) in the conversation that provides contextually relevant social and web search recommendations.
The vast amount of gathered genomic data from Microarray and other high throughput experiments ma... more The vast amount of gathered genomic data from Microarray and other high throughput experiments makes it extremely difficult for the researcher to interpret the data and form conclusions about the functions of the discovered genes. We can make use of extensive biomedical literature databases like Medline to find the functional similarity between genes using various information retrieval and clustering techniques.
Abstract. We propose a semi-supervised method to extract rule sentences from medical abstracts. M... more Abstract. We propose a semi-supervised method to extract rule sentences from medical abstracts. Medical rules are sentences that give interesting and nontrivial relationship between medical entities. Mining such medical rules is important since the rules thus extracted can be used as inputs to an expert system or in many more other ways. The technique we suggest is based on paraphrasing a set of seed sentences and populating a pattern dictionary of paraphrases of rules.
Abstract Extracting complex relationships automatically from unstructured information resources i... more Abstract Extracting complex relationships automatically from unstructured information resources is a challenging problem. It is an important problem in this present age of abundant machine processable information as there is a need to build intelligent knowledge-aware applications for tasks such search, extraction and reasoning. We have used Conditional Random Fields (CRFs) to identify various relationships from biomedical abstracts.
SVM was applied for classifying documents into epidemiology articles on human genes. This databas... more SVM was applied for classifying documents into epidemiology articles on human genes. This database is part of Genomics and Disease Prevention Information System and is maintained by the Center for Disease Control. This database is updated weekly by querying the PubMed, retrieving the articles, pruning them manually based on the title and then reading the rest of articles to classify them into positive set.
Abstract. Knowledge and user generated content is proliferating on the web in scientific publicat... more Abstract. Knowledge and user generated content is proliferating on the web in scientific publications, information portals and online social media. This knowledge explosion has continued to outpace technological innovation in efficient information access technologies. In this paper, we describe the methods and technologies for 'Conversational Search'as an innovative solution to facilitate easier information access and reduce the information overload for users.
Effective encoding of information is one of the keys to qualitative problem solving. Our aim is t... more Effective encoding of information is one of the keys to qualitative problem solving. Our aim is to explore Knowledge representation techniques that capture meaningful word associations occurring in documents. We have developed iReMedI, a TCBR based problem solving system as a prototype to demonstrate our idea. For representation we have used a combination of NLP and graph based techniques which we call as Shallow Syntactic Triples, Dependency Parses and Semantic Word Chains.
Abstract With the advent of open education resources, social networking technologies and new peda... more Abstract With the advent of open education resources, social networking technologies and new pedagogies for online and blended learning, we are in the early stages of a significant disruption in current models of education. The disruption is fueled by a staggering growth in demand. Open Social Learning systems open a new venue for self-motivated learners to access high quality learning materials.
ABSTRACT Cobot is a new intelligent agent platform that connects users through real-time and off-... more ABSTRACT Cobot is a new intelligent agent platform that connects users through real-time and off-line conversations about their health and medical issues. Intelligent web based information agents (conversational/community bots) participate in each conversation providing highly-relevant real-time informational recommendations and connecting people with relevant conversations and other community members.
Abstract We develop an innovative approach to delivering relevant information using a combination... more Abstract We develop an innovative approach to delivering relevant information using a combination of socio-semantic search and filtering approaches. The goal is to facilitate timely and relevant information access through the medium of conversations by mixing past community specific conversational knowledge and web information access to recommend and connect users and information together.
Abstract With an explosion in the proliferation of user-generated content in communities, informa... more Abstract With an explosion in the proliferation of user-generated content in communities, information overload is increasing and quality of readily available online content is deteriorating. There is an increasing need for intelligent systems that make use of implicit user generated knowledge in communities for community engagement. We describe our approach based on modeling user utterances in communities to proactively target the community for exchange of questions and answers.
Abstract. In this paper, we describe a Conversational Interaction framework as an innovative and ... more Abstract. In this paper, we describe a Conversational Interaction framework as an innovative and natural approach to facilitate easier information access by combining web search and recommendations. This framework includes an intelligent information agent (Cobot) in the conversation that provides contextually relevant social and web search recommendations.
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Papers by Saurav Sahay