Page Rank takes into account several dozen aspects (called features), amongst which are the density of the relation between different graph objects (hypertext links in the case of internet pages), the linguistic treatment of search terms, or the semantic analysis of the knowledge graph. We naturally took an interest in the work of the founders of Google on Page Rank, their algorithm. We, therefore, chose to isolate the search engine in a dedicated module on the platform and to turn it into a powerful innovation (and investment) zone. We decided from the get-go that a simple indexation system would prove limited and would fall short of providing the most relevant results for the users. ![]() The results often include false positives and the order in which the search comes out is over-represented with exact matches. In short, simple indexation is great for finding information whose characteristics are well known but falls short when the search is more exploratory. This approach is satisfactory when the user has a specific idea of what they are looking for (high intent search) but can prove disappointing when the search is more exploratory (low intent search) or when the idea is simply to spontaneously suggest relevant results to a user (no intent).
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