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It is based on the assembly fault occurrence model reflecting both product design and assembly shops.

The occurrence model is then extended to a two-dimensional medium by using appropriate two-dimensional variance function for the discrete random field.

We worked in four directions: (1) to create a co-occurrence model of unigrams and bigrams and use it as the baseline for the LSA model it was verified that LSA model was superior in both approaches; (2) to combine bigrams with LSA to test its performance, since traditional models only use unigrams.

The co-occurrence model outputs the two scores of co-occurrence for each article.

Furthermore, we use linear combination to adjust the co-occurrence model and the network-based model.

In our system, the development of the network-based model is closely tied to the effective use of the co-occurrence model.

In contrast to the co-occurrence model, the network-based model includes the PageRank and the betweenness in the same manner.

After calculating the scores from the co-occurrence model and the network-based model, we combine these two scores into the CoINindex for classifying curated articles.

The western extent of present-day suitable habitat in the niche-based occurrence model is fairly consistent with data recovered from material deposited in museum collections [ 13].

When the co-occurrence model and the network-based model used the frequency and PageRank, respectively, the best performance was 0.819 for the test set and 0.698 for the training set, respectively (α = 0.1, α = 0.3).

Despite the low overall success rate for our computational search (1/7 or 14%), these results demonstrated that the TFBS co-occurrence model we had defined was capable of enabling discovery of similar-acting CRMs [ 11].

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