Abstract: A new approach is proposed that contemplates systems and methods to examine and determine quality of objects cited by citations in a search result based on a citation graph that includes citing subjects, citations, and cited objects. First, influence scores of a plurality of subjects/sources that compose the citations of the objects in the search result are calculated. The quality of the objects cited by the subjects can then be determined by examining the influence scores for the subjects of the citations. Finally, the cited objects selected can be presented to a user or provided to a thirty party for further processing together with the relevant citations and citing subjects.

Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: A new approach is proposed that contemplates systems and methods to provide a ranking of cited objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of “experts” on “topics” without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

Abstract: A new approach is proposed that contemplates systems and methods to provide a ranking of citied objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of “experts” on “topics” without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

Abstract: A new approach is proposed that contemplates systems and methods to provide a ranking of citied objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of “experts” on “topics” without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: A new approach is proposed that contemplates systems and methods to examine and determine quality of objects cited by citations in a search result based on a citation graph that includes citing subjects, citations, and cited objects. First, influence scores of a plurality of subjects/sources that compose the citations of the objects in the search result are calculated. The quality of the objects cited by the subjects can then be determined by examining the influence scores for the subjects of the citations. Finally, the cited objects selected can be presented to a user or provided to a thirty party for further processing together with the relevant citations and citing subjects.

Abstract: A new approach is proposed that contemplates systems and methods to provide a ranking of citied objects and citing subjects identified as results of a search, where the relative expertise of subjects or sources of citations to said targets or objects is considered. The relative expertise is a function of the share of the subject's citations matching the query term or search criteria relative to the share of all subjects' citations matching the query term, weighted by the influence of the subjects. This allows the identification of “experts” on “topics” without any pre-defined categorization of topics or pre-computation of expertise. Under this novel approach, expertise can be determined on any query term in real-time.

Abstract: A new approach is proposed that contemplates systems and methods to determine temporality of a query in order to generate a search result including a list of objects that are not only based on matching of the objects to the query but also based on temporality analysis of the query. Here, the temporality of the query can be defined as the distribution over time of the objects matching the query, i.e., the chronology histogram of the query. Such distribution can be analyzed to provide a classification of the intent of the query. Classification of the intent of the query can result either in discrete classification of the query into categories, or in continuous classification of the query which may be a scalar or vector value resulting from transformations of the chronology histogram.

Abstract: A new approach is proposed that contemplates systems and methods to examine and determine quality of objects cited by citations in a search result based on a citation graph that includes citing subjects, citations, and cited objects. First, influence scores of a plurality of subjects/sources that compose the citations of the objects in the search result are calculated. The quality of the objects cited by the subjects can then be determined by examining the influence scores for the subjects of the citations. Finally, the cited objects selected can be presented to a user or provided to a thirty party for further processing together with the relevant citations and citing subjects.