Abstract: Pinnacle concepts are not amenable to detection by the use of keywords. A unit of natural language discourse (UNLD) “refers” to a pinnacle concept “C” when that UNLD uses linguistic expressions in such a way that “C” is regarded as expressed, used or invoked by an ordinary reader of “L.” A reference can have a “reference level” value that is proportional to: the “strength” with which the pinnacle concept is referenced, the probability that a pinnacle concept is referenced or both strength and probability. Pinnacle concepts can be divided into Quantifiers and non-Quantifiers. A Quantifier can modify the reference level assigned to a non-Quantifier. A concept “C,” that is determined to be referenced by a UNLD “x,” after application of its Quantifiers, is said to be asserted by “x.” Concept-based classification is the identification of whether a pinnacle concept “C” is asserted by a UNLD. Concept-based classification can be used for concept-based search.

Abstract: Determining themes is disclosed. Reputation data extracted from at least one data source is received. The reputation data includes a plurality of user-authored reviews. The presence of a first keyword is detected in a first review. The presence of a second keyword that is different from but associated with the first keyword is detected in a second review. A sentiment for a theme is determined based on the detected presence of the first and second keywords. A report that indicates the sentiment for the theme is provided as output.

Abstract: Determining themes is disclosed. Reputation data extracted from at least one data source is received. The reputation data includes a plurality of user-authored reviews. The presence of a first keyword is detected in a first review. The presence of a second keyword that is different from but associated with the first keyword is detected in a second review. A sentiment for a theme is determined based on the detected presence of the first and second keywords. A report that indicates the sentiment for the theme is provided as output.

Abstract: Pinnacle concepts are not amenable to detection by the use of keywords. A unit of natural language discourse (UNLD) “refers” to a pinnacle concept “C” when that UNLD uses linguistic expressions in such a way that “C” is regarded as expressed, used or invoked by an ordinary reader of “L.” A reference can have a “reference level” value that is proportional to: the “strength” with which the pinnacle concept is referenced, the probability that a pinnacle concept is referenced or both strength and probability. Pinnacle concepts can be divided into Quantifiers and non-Quantifiers. A Quantifier can modify the reference level assigned to a non-Quantifier. A concept “C,” that is determined to be referenced by a UNLD “x,” after application of its Quantifiers, is said to be asserted by “x.” Concept-based classification is the identification of whether a pinnacle concept “C” is asserted by a UNLD. Concept-based classification can be used for concept-based search.

Abstract: Concept-based ranking is applied to the results of a search process. Concept-based ranking relies on the input query, that produced the search results, having pinnacle concept properties specified for some of its keyword-based search terms. For each record “r” of a search result, it can be assigned a concept-based ranking score as follows. For each query term “QT,” of the input query, the following can be performed. The set of occurrences of “QT,” in the record, can be determined. Based upon the pinnacle concept of “QT,” and certain characteristics of the set of occurrences, a value can be assigned to “QT.” Characteristics, of the set of occurrences, can include the type of pinnacle concept asserted by at least one sub-unit of the record in which there is an occurrence. Once each “QT” has been assigned a value, such values can be combined to produce a score for ranking the record.

Abstract: Assigning sentiment to themes is disclosed. Reputation data extracted from at least one data source is received. The reputation data includes user-authored reviews. The user-authored reviews include text and at least one rating. For a first review included in the reputation data, at least one keyword is determined using the first review's text. A sentiment is assigned for a theme associated with the keyword based at least in part on the first review's rating.

Abstract: Performing detailed sentiment analysis includes generating a first sentiment score for a first entity based on a content source. The first sentiment score is generated with respect to a first dimension. A second sentiment score for the first entity is generated based on the content source. The second sentiment score is generated with respect to a second dimension.

Abstract: Pinnacle concepts are not amenable to detection by the use of keywords. A unit of natural language discourse (UNLD) “refers” to a pinnacle concept “C” when that UNLD uses linguistic expressions in such a way that “C” is regarded as expressed, used or invoked by an ordinary reader of “L.” A reference can have a “reference level” value that is proportional to: the “strength” with which the pinnacle concept is referenced, the probability that a pinnacle concept is referenced or both strength and probability. Pinnacle concepts can be divided into Quantifiers and non-Quantifiers. A Quantifier can modify the reference level assigned to a non-Quantifier. A concept “C,” that is determined to be referenced by a UNLD “x,” after application of its Quantifiers, is said to be asserted by “x.” Concept-based classification is the identification of whether a pinnacle concept “C” is asserted by a UNLD. Concept-based classification can be used for concept-based search.

Abstract: Searching computer-accessible content can be described as the utilization of an automated process to determine occurrences of where a sought-for concept is referred to in natural language discourse. Concept-based search refers to the reliable identification, within computer-accessible content that represents natural language discourse, of instances in which a particular pinnacle concept “C” is referenced. References to pinnacle concepts are not amenable to detection by the use of keywords. For each pinnacle concept “C,” whose reference is to be determined, a set of linguistic features can be compiled that is referred to herein as a “concept feature set.” In general, it is desirable for a concept feature set to be “complete.” A definition of completeness is presented. Concept-based search can be used in conjunction with keyword-based search.