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 generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity of chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have big influence on or enjoy high respect from the user will be ranked prominently in the search result presented to the user, thus biasing the search results from the user's perspective.

Abstract: A system, method, and machine readable medium are described for providing improved search functionality on a client device.

Abstract: A new approach is proposed that contemplates systems and methods to generate customized search results as well as metrics, such as aggregated sentiment, counts of targets or sources or citations, or aggregated gross impressions or exposure, of social media content items over a social network while discriminating between the perspectives of individuals from the media and individuals not from the media. This approach can be used to generate search results and/or metrics including only media perspectives, or excluding media perspectives. More specifically, while social media content items are retrieved from corpus based on certain search criteria, for the purpose of providing search results or providing aggregated metrics, the search criteria can include a media or non-media filter, which is applied to the authors posting social media content to exclude or include certain authors meeting media/non-media criteria.

Abstract: A new approach is proposed that contemplates systems and methods to generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity of chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have big influence on or enjoy high respect from the user will be ranked prominently in the search result presented to the user, thus biasing the search results from the users perspective.

Abstract: A new approach is proposed that contemplates systems and methods to generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity of chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have big influence on or enjoy high respect from the user will be ranked prominently in the search result presented to the user, thus biasing the search results from the user's perspective.

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 generate customized search results as well as metrics, such as aggregated sentiment, counts of targets or sources or citations, or aggregated gross impressions or exposure, of social media content items over a social network while discriminating between the perspectives of individuals from the media and individuals not from the media. This approach can be used to generate search results and/or metrics including only media perspectives, or excluding media perspectives. More specifically, while social media content items are retrieved from corpus based on certain search criteria, for the purpose of providing search results or providing aggregated metrics, the search criteria can include a media or non-media filter, which is applied to the authors posting social media content to exclude or include certain authors meeting media/non-media criteria.

Abstract: A new approach is proposed that contemplates systems and methods to provide a ranking of subjects or objects identified as results of a search, where “topicality specialization” and “relative topicality specialization” of the objects is computed and considered. The relative topicality specialization of an object is a function of the share of citations for the object matching the query term among all citations for all objects matching the query term. The computation of the topicality specialization and the relative topicality specialization for objects allow the identification of “specialized objects” for “topics” without any pre-defined categorization of topics or pre-computation of expertise.

Abstract: A new approach is proposed that contemplates systems and methods to provide query suggestions including real-time suggestion of complete query terms, which can be phrases, to a user by analyzing and indexing the real-time history/stream of content or documents in addition to the stream of queries entered. Since the real-time indexing generates a count of potential results for each term found and/or indexed in the stream, the terms found in that stream can then be used as potential query suggestions, knowing that it will be possible to provide results for those queries.

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 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 generate customized subjective search results from the perspective of a user who conducts the search or any other subject entity of chosen by the user. A scored subject list is created from the user's network of sources/subjects/contacts, where each element on the list is a subject/source and the score reflects the subject's potential influence or closeness of its connection/relation with the user. Once created, the subject list is then used as a bias filter on the list of citations from search results. With such influence-weighted citation scores, objects and/or subjects from citations of subjects that have big influence on or enjoy high respect from the user will be ranked prominently in the search result presented to the user, thus biasing the search results from the user's perspective.

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.