• Markowitz portfolio theory can be applied to determine budget allocation in paid online search advertising. Risk-adjusted performance advertising improved through diversification negatively correlated keywords. Average keyword popularity growth estimated from Google Trends is strongly related the standard deviation of for each (R 2 = 74%) a sample data 15 major sectors. The proposed approach ...

Abstract With the prevalence of Internet access and online services, various big graphs are generated in many real applications (e.g., social networks knowledge graphs). An important task on analyzing mining these is keyword search. Essentially, given a graph G query Q associated with set keywords, search aims to find substructure rooted tree or subgraph) S such that nodes collectively cover pa...

Keyword queries are those terms that users enter and use to retrieve documents that have all or any of those terms. They are the most familiar and popular method used by ordinary users to search data. Keyword queries are highly ambiguous. Keyword search querying has emerged as one of the most effective way for information discovery, especially over HTML documents in the World Wide Web. Because ...

Keyword spotting is a detection task consisting in discovering the presence of specific spoken words in unconstrained speech. The majority of keyword spotting systems are based on generative hidden Markov models and lack discriminative capabilities. However, discriminative keyword spotting systems are based on the estimation of a posteriori probabilities at the frame-level, hence they make use ...

Keyword spotting is a very forward-looking and promising branch of speech recognition. This paper presents a HMM-based keyword spotting system, which works with a new algorithm. The first discussion topic is the description of the search algorithm, that needs no representation of the non-keyword parts of the speech signal. For this purpose, the computation of the HMM scores and the Viterbi algo...