A method includes determining a plurality of topics corresponding to descriptive text and to comments concerning the descriptive text, wherein each of a number of sets of the plurality of topics comprise a similar topic and one or more supplemental topics. The method includes determining by a computer system probabilities for words, where the probabilities are that the words belong to individual ones of the topics. The method further includes generating, by the computer system and based on comments and the probabilities, a content summary comprising a plurality of comment snippets having positive and negative sentiments toward corresponding ones of the similar or supplemental topics in the sets of topics. Each topic has corresponding comment snippets having positive and negative sentiments. The method includes outputting by the computer system at least a portion of the plurality of topics and corresponding comment snippets. Apparatus and computer program products are also disclosed.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: determining a plurality of topics corresponding to descriptive text and to comments concerning the descriptive text, wherein each of a number of sets of the plurality of topics comprise a similar topic and one or more supplemental topics; determining by a computer system probabilities for words, where the probabilities are that the words belong to individual ones of the topics; generating, by the computer system and based on comments and the probabilities, a content summary comprising a plurality of comment snippets having positive and negative sentiments toward corresponding ones of the similar or supplemental topics in the sets of topics, wherein each topic has corresponding comment snippets having positive and negative sentiments; and outputting by the computer system at least a portion of the plurality of topics and corresponding comment snippets. 2. The method of claim 1, wherein outputting further comprises formatting the descriptive text and the comments to be suitable for display at least in part on a single webpage. 3. The method of claim 2, wherein the portion of the plurality of topics and corresponding comment snippets are part of a comments digest and the comments digest is reachable using at least one link on the webpage. 4. The method of claim 2, wherein the portion of the plurality of topics and corresponding comment snippets are part of a comments digest and the comments digest is viewable at least in part on the webpage. 5. The method of claim 1, wherein determining probabilities for words further comprises performing an estimating process that estimates the probabilities that the words belong to individual ones of the topics, and during the estimating process, in response to words being present in the descriptive text, updating a probability distribution for the words according to their prior probability in the descriptive text, otherwise updating the probability distribution for the words according to a previous iteration of the estimating process. 6. The method of claim 5, wherein determining probabilities for words further comprises determining supplemental topics not resembling descriptive information in the descriptive text. 7. The method of claim 5, further comprising, prior to generating the content summary, performing language pre-processing to remove repetitions of characters in words and correcting spelling of resultant words with repetitions of characters removed. 8. The method of claim 1, wherein the comment snippets are sentences and generating a comment summary further comprises assigning sentences from the comments into corresponding ones of the topics based on probabilities of the sentences, the probabilities indicating how probable it is the sentences belong to a corresponding topic. 9. The method of claim 8, wherein generating the comment summary further comprises selecting the sentences with positive sentiment based on positive aspects of topics to which the sentences correspond and selecting the sentences with negative sentiment based on negative aspects of topics to which the sentences correspond. 10. The method of claim 8, wherein generating the comment summary further comprises examining dependency tree structures of the sentences to determine sentiment polarities of each of the sentences. 11. The method of claim 1, wherein outputting comprises storing the at least the portion of the plurality of topics and corresponding comment snippets in a memory of the computer. 12. The method of claim 1, wherein outputting comprises outputting the at least the portion of the plurality of topics and corresponding comment snippets in a format suitable for display on a display. 13. A computer program product comprising a computer-readable storage medium bearing computer program code embodied therein for use with a computer, the computer program code comprising: code for determining a plurality of topics corresponding to descriptive text and to comments concerning the descriptive text, wherein each of a number of sets of the plurality of topics comprise a similar topic and one or more supplemental topics; code for determining by a computer system probabilities for words, where the probabilities are that the words belong to individual ones of the topics; code for generating, by the computer system and based on comments and the probabilities, a content summary comprising a plurality of comment snippets having positive and negative sentiments toward corresponding ones of the similar or supplemental topics in the sets of topics, wherein each topic has corresponding comment snippets having positive and negative sentiments; and code for outputting by the computer system at least a portion of the plurality of topics and corresponding comment snippets. 14. An apparatus, comprising: one or more processors; and one or more memories including computer program code, the one or more memories and the computer program code configured, with the one or more processors, to cause the apparatus to perform at least the following: determining a plurality of topics corresponding to descriptive text and to comments concerning the descriptive text, wherein each of a number of sets of the plurality of topics comprise a similar topic and one or more supplemental topics; determining probabilities for words, where the probabilities are that the words belong to individual ones of the topics; generating, based on comments and the probabilities, a content summary comprising a plurality of comment snippets having positive and negative sentiments toward corresponding ones of the similar or supplemental topics in the sets of topics, wherein each topic has corresponding comment snippets having positive and negative sentiments; and outputting at least a portion of the plurality of topics and corresponding comment snippets. 15. The apparatus of claim 14, wherein outputting further comprises formatting the descriptive text and the comments to be suitable for display at least in part on a single webpage. 16. The apparatus of claim 15, wherein the portion of the plurality of topics and corresponding comment snippets are part of a comments digest and the comments digest is reachable using at least one link on the webpage. 17. (canceled) 18. The apparatus of claim 14, wherein determining probabilities for words further comprises performing an estimating process that estimates the probabilities that the words belong to individual ones of the topics, and during the estimating process, in response to words being present in the descriptive text, updating a probability distribution for the words according to their prior probability in the descriptive text, otherwise updating the probability distribution for the words according to a previous iteration of the estimating process. 19. (canceled) 20. (canceled) 21. The apparatus of claim 14, wherein the comment snippets are sentences and generating a comment summary further comprises assigning sentences from the comments into corresponding ones of the topics based on probabilities of the sentences, the probabilities indicating how probable it is the sentences belong to a corresponding topic. 22. (canceled) 23. (canceled) 24. The apparatus of claim 14, wherein outputting comprises storing the at least the portion of the plurality of topics and corresponding comment snippets in the one or more memories of the apparatus. 25. The apparatus of claim 14, wherein outputting comprises outputting the at least the portion of the plurality of topics and corresponding comment snippets in a format suitable for display on a display.