A method and system of inferential-based communications applies two sets of values, whereby the first set of values are determined from inferences of the relevancy of textual elements with respect to text-based content and the second set of values are determined from behavioral-based inferences with respect to topics, so as to select appropriate words to be included in communications that are generated for delivery to a user. The inferences that are with respect to text-based content may be determined by applying analytic methods such as Bayesian or statistical learning-based methods. The values that are determined from behavioral-based inferences with respect to topics may correspond to inferences of interest and/or expertise. Words in the communications may be selected and/or arranged in accordance with syntactical rules and may reference elements of the text-based content and/or behavioral inferences.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method, comprising: accessing automatically a first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing text that is associated with a content object, wherein each of the plurality of values is based upon an automatically inferred degree of relevancy between an element of the text and the content object; accessing automatically a second plurality of values, wherein each of the second plurality of values corresponds to one or more topics of a plurality of topics, and wherein a magnitude of each of the second plurality of values is based upon an automatically determined inference from one or more user behaviors; and generating automatically a communication for delivery to a user of a computer-implemented system, wherein the communication comprises a plurality of words, wherein the plurality of words are selected in accordance with the first plurality of values, the second plurality of values, and one or more syntactical rules. 2. The method of claim 1, further comprising: accessing automatically the first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing the text that is associated with the content object, wherein each of the plurality of values is based upon the automatically inferred degree of relevancy between the element of the text and the content object, wherein the inferred degree of relevancy is based upon a frequency analysis of words or phrases within the text. 3. The method of claim 1, further comprising: accessing automatically the first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing the text that is associated with the content object, wherein each of the plurality of values is based upon the automatically inferred degree of relevancy between the element of the text and the content object, wherein the inferred degree of relevancy is determined by applying a statistical learning algorithm. 4. The method of claim 1, further comprising: generating the communication, wherein the communication is generated in response to a search request performed by the user. 5. The method of claim 4, further comprising: accessing automatically the second plurality of values, wherein at least one of the second plurality of values is associated with an inferred expertise level. 6. The method of claim 5, further comprising: generating the communication, wherein the communication refers to the inferred expertise level. 7. The method of claim 1, further comprising: generating the communication that comprises the plurality of words, wherein at least one of the plurality of words comprises an element of the text. 8. A computer-implemented system comprising one or more processor-based devices configured to: access a first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing text that is associated with a content object, wherein each of the plurality of values is based upon an automatically inferred degree of relevancy between an element of the text and the content object; access a second plurality of values, wherein each of the second plurality of values corresponds to one or more topics of a plurality of topics, and wherein a magnitude of each of the second plurality of values is based upon an automatically determined inference from one or more user behaviors; and generate a communication for delivery to a user of the computer-implemented system, wherein the communication comprises a plurality of words, wherein the plurality of words are selected in accordance with the first plurality of values, the second plurality of values, and one or more syntactical rules. 9. The system of claim 8, further comprising the one or more processor-based devices configured to: access the first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing the text that is associated with the content object, wherein each of the plurality of values is based upon the automatically inferred degree of relevancy between the element of the text and the content objects, wherein the inferred degree of relevancy is determined by applying a Bayesian method. 10. The system of claim 8, further comprising the one or more processor-based devices configured to: access the second plurality of values, wherein at least one of the second plurality of values is associated with an inferred interest level. 11. The system of claim 10, further comprising the one or more processor-based devices configured to: access the second plurality of values, wherein at least one of the second plurality of values is associated with an inferred expertise level. 12. The system of claim 11, further comprising the one or more processor-based devices configured to: generate the communication comprising the plurality of words, wherein at least one of the plurality of words is selected to convey a level of confidence with respect to the communication, wherein the level of confidence is based upon an automatic assessment of the quantity of user behaviors from which the expertise level is inferred. 13. The system of claim 8, further comprising the one or more processor-based devices configured to: generate the communication comprising the plurality of words, wherein the plurality of words are arranged in accordance with the one or more syntactical rules. 14. The system of claim 13, further comprising the one or more processor-based devices configured to: generate the communication comprising the plurality of words, wherein at least one of the plurality of words is selected to convey a theme that is derived from one or more of the elements of text. 15. A computer-implemented system comprising one or more processor-based devices configured to: access a first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing text that is associated with a content object, wherein each of the plurality of values is based upon an automatically inferred degree of relevancy between an element of the text and the content object; access a second plurality of values, wherein the second plurality of values are automatically generated from the first plurality of values, wherein each of the second plurality of values is based upon an inferred degree of relationship between the content object and one or more topics of a plurality of topics; access a third plurality of values, wherein each of the third plurality of values corresponds to one or more topics of the plurality of topics, and wherein a magnitude of each of the third plurality of values is based upon an automatically determined inference from one or more user behaviors; and generate a communication for delivery to a user, wherein the communication comprises a plurality of words, wherein the plurality of words are selected in accordance with the second plurality of values and the third plurality of values. 16. The system of claim 15, further comprising the one or more processor-based devices configured to: access the first plurality of values, wherein each of the first plurality of values is determined by automatically analyzing the text that is associated with the content object, wherein each of the plurality of values is based upon the automatically inferred degree of relevancy between the element of the text and the content object, wherein the inferred degree of relevancy is determined by an automatic statistical analysis. 17. The system of claim 15, further comprising the one or more processor-based devices configured to: access the second plurality of values, wherein the second plurality of values are automatically generated from the first plurality of values, wherein each of the second plurality of values is based upon the inferred degree of relationship between the content object and one or more topics, wherein the one or more topics are determined by applying a computer-implemented neural network to one or more content objects. 18. The system of claim 15, further comprising the one or more processor-based devices configured to: access the second plurality of values, wherein the second plurality of values are automatically generated from the first plurality of values, wherein the automatic generation is facilitated by a lexicon-based mapping between an element of the text and at least one of the one or more topics. 19. The system of claim 15, further comprising the one or more processor-based devices configured to: access the third plurality of values, wherein at least one of the third plurality of values is associated with an inferred expertise level. 20. The system of claim 15, further comprising the one or more processor-based devices configured to: generate the communication comprising the plurality of words, wherein the plurality of words are arranged in accordance with one or more syntactical rules.