Sentence examples for orientation of a document from inspiring English sources

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

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.

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

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.

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).

We approach the task of estimating the sentiment orientations of a collection of documents as a text classification problem.

The profit orientation is only one orientation of a person.

d Orientation of a triangular geometry.

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.