Linguistically aware link analysis method and system

A method of ranking a set of candidate pages in response to a search query, the method comprising the steps of:

• identifying the candidate pages from a network that potentially match the search query;
• assigning a content-based relevance rank to each candidate page based on a probability that a user will stay on a selected candidate page;
• adjusting the content-based relevance rank of each candidate page where the content-based relevance rank for a selected candidate page is influenced by a quantity and relevance of candidate pages that point to the selected candidate page;
• and
• ranking the candidate pages based on the adjusted content-based relevance rank.

A method of ranking a set of candidate pages in response to a search query, the method comprising the steps of:

• identifying the candidate pages from a network that potentially match the search query;
• assigning a content-based relevance rank to each candidate page based on a probability that a user will stay on a selected candidate page;
• adjusting the content-based relevance rank of each candidate page where the content-based relevance rank for a selected candidate page is influenced by a quantity and relevance of candidate pages that point to the selected candidate page, wherein the adjusting includes determining, for each candidate page, a probability of a user being on a page in relation to all candidate pages, the probability of a user being on a page being set as the adjusted content-based relevance rank for that page;
• and
• ranking the candidate pages based on the adjusted content-based relevance rank.

A system for determining a relevance rank for each page of a candidate set of pages identified by a search query, the system comprising:

• an information retrieval system for identifying the candidate set of pages from a network in response to the search query;
• content analyzer logic for obtaining a content-based relevance rank for each of the pages based on a content of each page;
• and
• a relevance rank analyzer for obtaining a relevance rank for each page where the relevance rank for a selected page being obtained by combining the content-based relevance rank of the selected page with distributed values of the content-based relevance rank from one or more pages that point to the selected page where the distributed values include a link analysis rank from in-coming page links, where the link analysis rank being determined from the distributed values of content-based relevance from the one or more pages that point to the selected page.

A system for determining a relevance ranking for pages obtained from a network search query, the system comprising:

• link structure logic for obtaining a link structure of the pages which identifies out-going links from each of the pages which become in-coming links to other pages;
• a content analyzer for determining a content of each page;
• a content relevance ranking logic for determining a content relevance rank for each page based on a content of the page in relation to the network query;
• link analysis logic for determining a link ranking for each of the out-going links for each of the pages, the link ranking for a selected page representing a probability of leaving the selected page by the out-going link;
• and
• a relevance rank adjuster for determining and adjusting a relevance rank of a page by combining the content relevance rank with the link rankings associated to in-coming links for the page.

A system for determining a relevance rank for each page of a candidate set of pages identified by a search query where the system is embodied as a computer-readable medium that provides processor executable instructions, the system comprising:

• an information retrieval system for identifying the candidate set of pages from a network in response to the search query;
• content analyzer logic for obtaining a content-based relevance rank for each of the pages based on a content of each page;
• and
• a relevance rank analyzer for obtaining a relevance rank for each page where the relevance rank for a selected page being obtained by combining the content-based relevance rank of the selected page with distributed values of the content-based relevance rank from one or more pages that point to the selected page where the distributed values include a link analysis rank from in-coming page links, where the link analysis rank being determined from distributed values of content-based relevance from one or more pages that point to the selected page.

A computer-readable medium for providing processor executable instructions operable to perform a method of determining a relevance rank of a plurality of pages identified by a search query, the method comprising:

• identifying a candidate set of pages in response to the search query;
• determining a content-based relevance rank for each of the pages based on a content of each page;
• and
• adjusting the content-based relevance rank for a selected page from the candidate set of pages by distributing the content-based relevance rank from one or more pages that point to the selected page where the distributing is based on a link structure of the pages including link rank values from in-coming links where the link rank values are determined from distributed values of content-based relevance from one or more pages that point to the selected page.

A computer-readable medium for providing processor executable instructions operable to perform a method of ranking a set of candidate pages in response to a search query, the method comprising the steps of:

• identifying the candidate pages from a network that potentially match the search query;
• assigning a content-based relevance rank to each candidate page based on a probability that a user will stay on a selected candidate page;
• adjusting the content-based relevance rank of each candidate page where the content-based relevance rank for a selected candidate page is influenced by a quantity and relevance of candidate pages that point to the selected candidate page;
• and
• ranking the candidate pages based on the adjusted content-based relevance rank.