Abstract: A directed set can be used to establish contexts for linguistic concepts: for example, to aid in answering a question, to refine a query, or even to determine what questions can be answered given certain knowledge. A directed set includes a plurality of elements and chains relating the concepts. One concept is identified as a maximal element. The chains connect the maximal element to each concept in the directed set, and more than one chain can connect the maximal element to any individual concept either directly or through one or more intermediate concepts. A subset of the chains is selected to form a basis for the directed set. Each concept in the directed set is measured to determine how concretely each chain in the basis represents it. These measurements for a single concept form a vector in Euclidean k-space. Distances between these vectors can be used to determine how closely related pairs of concepts are in the directed set.

Abstract: Codifying the “most prominent measurement points” of a document can be used to measure semantic distances given an area of study (e.g., white papers on some subject area). A semantic abstract is created for each document. The semantic abstract is a semantic measure of the subject or theme of the document providing a new and unique mechanism for characterizing content. The semantic abstract includes state vectors in the topological vector space, each state vector representing one lexeme or lexeme phrase about the document. The state vectors can be dominant phrase vectors in the topological vector space mapped from dominant phrases extracted from the document. The state vectors can also correspond to words in the document that are most significant to the document's meaning (the state vectors are called dominant vectors in this case). One semantic abstract can be directly compared with another semantic abstract, resulting in a numeric semantic distance between the semantic abstracts being compared.

Abstract: Starting with a dictionary including concepts and chains, a subset of the chains is selected as intentional stance basis chains (ISBCs). Concepts in the dictionary are chosen and mapped to state vectors using the ISBCs. The state vectors are assembled into a template, and an action and threshold distance are assigned to the template. When an impact summary is generated for a content source, the distance between the impact summary and the template is measured. If the distance is less than the threshold distance associated with the action for the template, the action is performed.

Abstract: A directed set can be used to establish contexts for linguistic concepts: for example, to aid in answering a question, to refine a query, or even to determine what questions can be answered given certain knowledge. A directed set includes a plurality of elements and chains relating the concepts. One concept is identified as a maximal element. The chains connect the maximal element to each concept in the directed set, and more than one chain can connect the maximal element to any individual concept either directly or through one or more intermediate concepts. A subset of the chains is selected to form a basis for the directed set. Each concept in the directed set is measured to determine how concretely each chain in the basis represents it. These measurements for a single concept form a vector in Euclidean k-space. Distances between these vectors can be used to determine how closely related pairs of concepts are in the directed set.

Abstract: State vectors representing the semantic content of a document are created. The state vectors are superpositioned to construct a single vector representing a semantic abstract for the document. The single vector can be normalized. Once constructed, the single vector semantic abstract can be compared with semantic abstracts for other documents to measure a semantic distance between the documents, and can be used to locate documents with similar semantic content.

Abstract: Starting with a dictionary including concepts and chains, a subset of the chains is selected as intentional stance basis chains (ISBCs). Concepts in the dictionary are chosen and mapped to state vectors using the ISBCs. The state vectors are assembled into a template, and an action and threshold distance are assigned to the template. When an impact summary is generated for a content source, the distance between the impact summary and the template is measured. If the distance is less than the threshold distance associated with the action for the template, the action is performed.

Abstract: Codifying the “most prominent measurement points” of a document can be used to measure semantic distances given an area of study (e.g., white papers on some subject area). A semantic abstract is created for each document. The semantic abstract is a semantic measure of the subject or theme of the document providing a new and unique mechanism for characterizing content. The semantic abstract includes state vectors in the topological vector space, each state vector representing one lexeme or lexeme phrase about the document. The state vectors can be dominant phrase vectors in the topological vector space mapped from dominant phrases extracted from the document. The state vectors can also correspond to words in the document that are most significant to the document's meaning (the state vectors are called dominant vectors in this case). One semantic abstract can be directly compared with another semantic abstract, resulting in a numeric semantic distance between the semantic abstracts being compared.

Abstract: As content flows across a computer network, the content stream is monitored and compared with a template. If the content stream comes within a threshold distance of the template, a policy is enforced on the network.

Abstract: A directed set can be used to establish contexts for linguistic concepts: for example, to aid in answering a question, to refine a query, or even to determine what questions can be answered given certain knowledge. A directed set includes a plurality of elements and chains relating the concepts. One concept is identified as a maximal element. The chains connect the maximal element to each concept in the directed set, and more than one chain can connect the maximal element to any individual concept either directly or through one or more intermediate concepts. A subset of the chains is selected to form a basis for the directed set. Each concept in the directed set is measured to determine how concretely each chain in the basis represents it. These measurements for a single concept form a vector in Euclidean k-space. Distances between these vectors can be used to determine how closely related pairs of concepts are in the directed set.

Abstract: In a hierarchically organized distributed file system, resources belong to the containers in which they are located. These resources do not have to be co-located with the, containers in which they are stored, but can be distributed over the file system. To locate a desired resource, the unique name of the resource is determined. Moving upward through the containers in the hierarchically organized distributed file system, the lowest container with a location service is determined. The location service is queried for known instances of the resource. Any instance of the resource returned from the location service can then be utilized. Semantic contexts can also be applied to the network to control access or usage of both the location services and resource instances. The use of semantic contexts allows for improvements in network usage, security, resource allocation, and the like.

Abstract: A content stream having a plurality of phrases is accessed. One or more phrases in the content stream are marked. For example, the phrases may be annotated and/or highlighted. The marked one or more phrases are extracted and are processed to determine semantic information. A token is created based on the semantic information. Such a token might be used as part of a method for assigning semantic characterization to a content stream. For example, the token could be associated with one or more profiles. At least a portion of the content stream could be represented in a semantic space corresponding to one or more profiles, and/or a semantic record might be instantiated from the profiles and compared with other semantic records.

Abstract: A method and system for license authentication over a network. An on-line vendor receives a digital certificate that includes a public key associated with a consumer, and a digital signature of the consumer. A license packet is generated that includes a unique serial number. A record that includes the digital certificate is stored in a memory. The license packet is optionally encrypted with the public key associated with the consumer, and the license packet is forwarded to the consumer. When a post-sale service is required, the consumer generates a request that includes the digital signature of the consumer, and the request is forwarded to the vendor. The vendor accesses the memory to authenticate that the request was sent by the consumer, and if so, the service request is fulfilled.

Abstract: A method in a system comprises accessing a content stream and parsing the content stream into phrases. One or more tokens are determined, at least partially based on the extracted phrases. One or more profiles are associated with the tokens. One or more semantic records are instantiated from the profiles. The semantic record is compared with other semantic records.