Besides LDA (Latent Dirichlet allocation), are there other ways or methods to detect a topic or category from a sentence?
For example, all the categories or tags from news websites can be used to train a classifier to predict the topic for a new sentence or article or a paragraph.
Are there any known public datasets with keywords to topics relationship which can be used a training set in a classic classification problem?
A simple training data example of a news website:
Article 1: category x Article 2: category x Article 3: category x Article 4: category y Article 5: category y Article 6: category y
It's a very simple example but it's enough to paint the picture. Now use this data to predict the category of a new article.
A bit of explanation: By topic I mean if a text is talking about politics, entertainment, business, finance, lifestyle etc and ideally, a classification into sub-categories of such types. A similar categorization is used in the news website where they place each article in a specific category.