PageRank is primarily based on link structure analysis. Recently, it has been shown that content information can be utilized to improve link analysis. We propose a novel algorithm that harnesses the information contained in the history of a surfer to determine his topic of interest when he is on a given page. As the history is unavailable until query time, we guess it probabilistically so that ...

As a rapidly booming industry in recent years, the key problem for Search Engine Marketing (SEM) is to extract web page attributes contributed to the ranking in search engine such as Google and Baidu. The quantitative analysis of these agricultural page attributes is aimed in this paper and the attribute extractor in Java platform is built. Meantime, in order to gain a sample set, a batch gaini...

Graph ranking plays an important role in many applications, such as page ranking on web graph and entity ranking on social networks. In the applications, besides graph structure, rich information on nodes and edges and explicit or implicit human supervision are often available. In contrast, conventional algorithms (e.g., PageRank and HITS) compute ranking scores by only resorting to graph struc...

When someone wishes to find the lyrics for a song they typically go online and use a search engine. There are a large number of lyrics available on the internet as the effort required to transcribe and post lyrics is minimal. These lyrics are promptly returned to the user with customary search engine page ranking formula deciding the ordering of these results based on links, views, clicks, etc....

When faced with a poor set of document summaries on the first page of returned search results, a user may respond in various ways: by proceeding on to the next page of results; by entering another query; by switching to another service; or by abandoning their search. We analyse this aspect of searcher behaviour using a commercial search system, comparing a deliberately degraded system to the or...

Web page ranking requires the optimization of sophisticated performance measures. Current approaches only minimize measures indirectly related to performance scores. We present a new approach which allows optimization of an upper bound of the appropriate loss function. This is achieved via structured estimation, where in our case the input corresponds to a set of documents and the output is a r...

We study methods for extracting importance scores for nodes on a directed graph, using only the topology of the graph as a guide. Such ranking has many applications in directed networks. Our strategy is to find an eigenvector, which is positive everywhere on the graph and can be in interpreted as a global importance function for its topological content, avoiding significant modification of the ...

The rapid growth of the Web has led to the development of many techniques for enhancing search rankings by using precomputed numeric document attributes such as the estimated popularity or importance of Web pages. For efficient keyword-search query processing over large document repositories, it is vital that these auxiliary attribute vectors, containing numeric per-document properties, be kept...

When a database query has a large number of results, the user can only be shown one page of results at a time. One popular approach is to rank results such that the “best” results appear first. However, standard database query results comprise a set of tuples, with no associated ranking. It is typical to allow users the ability to sort results on selected attributes, but no actual ranking is de...

The TREC 2003 web track consisted of both a non-interactive stream and an interactive stream. Both streams worked with the .GOV test collection. The non-interactive stream continued an investigation into the importance of homepages in Web ranking, via both a Topic Distillation task and a Navigational task. In the topic distillation task, systems were expected to return a list of the homepages o...