Sentence examples for orientation of document from inspiring English sources

We wish to learn a vector c∈ℜ|V| such that the classifier orient = sign cTx) accurately estimates the sentiment orientation of document x, returning +1 (-1) for documents expressing positive (negative) sentiment about the topic of interest.

Each method formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and enables prior knowledge concerning the sentiment orientation of documents or words of interest to be effectively combined with "auxiliary" information to produce accurate sentiment estimates.

Machine learning (ML) involves building models from labeled training dataset (instances of texts or sentences) in order to determine the orientation of a document.

You can adjust the orientation of the document (portrait or landscape) using the Orientation menu in the Layout tab.

Estimate the sentiment orientation of any new document × of interest as: orient = sign cTx).  .

Estimate the sentiment orientation of any new document × of interest as: orient = sign cTx).

Each method formulates the task as one of text classification, models the data as a bipartite graph of documents and words, and assumes that only limited prior information is available regarding the sentiment orientation of any of the documents or words of interest.

Lexicon analysis aims to calculate the polarity of a document from the semantic orientation of words or phrases in the document.

Sentiment analysis could be divided into two main categories: Lexicon analysis aims to calculate the polarity of a document from the semantic orientation of words or phrases in the document.

The orientation of the highest qualification is documented in a separate variable in the PIAAC data, which was derived from the national educational attainment questions ex-post.

The document model consists of document types.