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Search-based advertising services provided by search engines enable companies to promote their products to internet users based on their queries is now a major online advertising channel. In most search based advertising services, a company sets a budget, selects keywords, bid for each keyword and pay for each click
Sponsored Search allows companies to place text advertisements for selected keywords on Search Engine Results Pages (SERPs). The objective of the present research is to determine whether and under what circumstances it makes sense, in economic terms, for brand owners to pay for sponsored search ads for their brand
One of the most serious problems that conventional knowledge management (KM) encompasses has been pointed out tardy and ineffective acquisition of knowledge. To resolve this problem, knowledge must be autonomously acquired according to its context of use by applying the technique of keyword extraction in machine
, for example) don't even enable keyword searches on their sites. The Web's increasingly dynamic nature complicates searching. New pages created on the fly using personalization information, and even static content, with dynamically inserted sidebars, navigation bars, advertising and commentary, can present a rapidly
In search engine advertising, the right selection of keywords is one of the most important step to maximize the advertisers' profitability. Keyword suggestion methodologies are used to map the advertisers selection of keywords and the recent popular queries using statistical data. In this project we are trying to
We analyze email communications within a large company to reveal how email activity patterns depend on content. We characterize email contents using keywords and examine statistics of email transmissions. As a result, we are able to identify differences in network structures and propagation behaviors depending on the
to external hierarchical resource to polish accuracy of text matching. Also, a whole framework of text processing, keyword extraction and information matching is applied firstly among Chinese SMEs complementarity identification. By using machine learning algorithm, complementarities are digitalized and potential
lattice is introduced and used to guess the cause. Two cases of interactive and iterative process are shown where a user proceeds from a simple query to a new hypothesis, which would not be able to found by a naive cross tabulation or keyword extraction.
to collect active commercial entities and a commercial relation lexicon is created to collect keywords that flag commercial relations. Illustration and applications are also discussed, which undoubtedly discloses a promising future of commercial network study.
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