1. A computer-implemented method comprising: segmenting textual content for each of a plurality of distinct book content items into word strings, each word string including a predefined number of contiguous words in the textual content of a book content item; classifying word strings having a frequency of occurrence that is less than a threshold frequency of occurrence as uncommon word strings, the frequency of occurrence for each word string being a number of occurrences of the word string relative to the total number of word strings in the plurality of distinct book content items; representing a weighted graph in computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching uncommon word string, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching word strings in the textual content of other distinct book content items that are represented by other distinct nodes, each matching word string being a word string that matches an uncommon word string in the textual content of the distinct book content item corresponding to the distinct node; and generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of an uncommon word string to one or more matching word strings in the textual content of another distinct book content item; and determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items.
1. A computer-implemented method comprising: segmenting textual content for each of a plurality of distinct book content items into word strings, each word string including a predefined number of contiguous words in the textual content of a book content item; classifying word strings having a frequency of occurrence that is less than a threshold frequency of occurrence as uncommon word strings, the frequency of occurrence for each word string being a number of occurrences of the word string relative to the total number of word strings in the plurality of distinct book content items; representing a weighted graph in computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, and where an edge exists in the weighted graph between each pair of distinct nodes that represent distinct book content items that both include a matching uncommon word string, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching word strings in the textual content of other distinct book content items that are represented by other distinct nodes, each matching word string being a word string that matches an uncommon word string in the textual content of the distinct book content item corresponding to the distinct node; and generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of an uncommon word string to one or more matching word strings in the textual content of another distinct book content item; and determining a rank score for each distinct book content item based on the edges between the distinct nodes representing the distinct book content items, the rank score being a score indicative of the importance of each distinct book content item relative to other distinct book content items. 8. The method of claim 1 , further comprising ranking the distinct nodes based on the edge weights.