Abstract: The present invention provides a method, and an associated apparatus configured to implement such a method, for analysing mark-up language text content, such as might be found on a website or within online user generated content. The method comprises a training phase, in which plurality of schemas are automatically generated from a specified text and a final schema is compiled. This final schema can then be used to compare with other online text content such that content which matched the final schema can be identified, for example for further analysis and comparison.

Abstract: A method of comparing the semantic similarity of two different text phrases in which the grammatical structure of the two different text phrases is analyzed and a keyword set for each of the different text phrases is derived The semantic similarity of the phrases can be determined in accordance with the grammatical structure of the two different text phrases and the contents of the two keyword sets.

Abstract: The present invention provides a method, and a system, for analysing a textual passage and classifying it against a number of predetermined categories. In the event that the text passage under analysis is not sufficiently similar to any of the predetermined categories then it will be classified as belonging to a further category.

Abstract: A method of comparing the semantic similarity of two different text phrases in which the grammatical structure of the two different text phrases is analysed and a keyword set for each of the different text phrases is derived The semantic similarity of the phrases can be determined in accordance with the grammatical structure of the two different text phrases and the contents of the two keyword sets.

Abstract: Methods and systems for identifying data patterns from data comprising at least one data object, said data having at least one existing pattern class associated therewith, said data object being represented by a base feature vector, at least one of said base feature vectors having a structure of higher-level and lower-level feature vectors such that at least one element of a higher-level feature vector is itself a lower-level feature vector.

Abstract: Methods and systems for identifying data patterns from data comprising at least one data object, said data having at least one existing pattern class associated therewith, said data object being represented by a base feature vector, at least one of said base feature vectors having a structure of higher-level and lower-level feature vectors such that at least one element of a higher-level feature vector is itself a lower-level feature vector.

Abstract: Appropriate updates to a respective user profile are inferred from monitored user activity. Such updates are suitable for use with applications programs that customize services based upon data and attributes stored in a user profile. The apparatus is arranged to personalize various aspects of a preferred profile updating process on the basis of stored user preferences, applying meta-rules to apply those user preferences to the definition of a set of personalized rule weights to be applied in a fuzzy inference process that infers profile updates by applying fuzzy rules and fuzzy sets to the analysis of event statistics derived from the results of user monitoring. The personalized rule weights are applied to selectively adjust the effect of particular fuzzy rules. In addition, mapping of event statistics to fuzzy rule premises in the fuzzy inference process may be personalized through the use of user-defined fuzzy sets.

Abstract: A method and apparatus are provided to infer, from monitored user activity, appropriate updates to a respective user profile. The method and apparatus are suitable for use with applications programs that customise services based upon data and attributes stored in a user profile. The apparatus is arranged to personalise various aspects of a preferred profile updating process on the basis of stored user preferences, applying meta-rules to apply those user preferences to the definition of a set of personalised rule weights to be applied in a fuzzy inference process that infers profile updates by applying fuzzy rules and fuzzy sets to the analysis of event statistics derived from the results of user monitoring. The personalised rule weights are applied to selectively adjust the effect of particular fuzzy rules. In addition, mapping of event statistics to fuzzy rule premises in the fuzzy inference process may be personalised through the use of user-defined fuzzy sets.

Abstract: A profile management system, for use with information processing applications which retrieve information on behalf of a user. The system comprises a profile generator which generates default user profiles. The profile generator can identify user-specific information from, for instance, an organisation chart such that new members of an organisation are automatically assigned a profile. This enables information processing applications to provide new members with information that is relevant to their role within an organisation.

Abstract: A profile management system, for use with information processing applications which retrieve information on behalf of a user. The system comprises a profile generator which generates default user profiles. The profile generator can identify user-specific information from, for instance, an organisation chart such that new members of an organisation are automatically assigned a profile. This enables information processing applications to provide new members with information that is relevant to their role within an organisation.