The Heroku apps site is for running web apps. I'm aiming to convert research software, usually sitting in repositories, into more usable versions this way. It can take a few seconds to start up.
The idea is that the apps are discrete tools that could be used in combination with each other, so the output of some apps can be copy-pasted to be input for others.
Currently, the apps include:
- A set of Natural Language Processing scripts/apps online, all based on word embedding vectors.
- "SemSim" is a kind of semantic filter, calculating the similarity of each a list of target words with one versus another set of "attribute" words.
- "SemTag" assigns tags to the content of a text, as a whole and per paragraph (by default, emotion-words are used as tags).
- "SemNull" gives a null hypothesis distribution for similarity scores over randomly selected words, given a specified role in a template sentence.
- "SemCluster" finds clusters of words with simlar meanings (a kind of automated affinity mapping).
A conceptual explanation of these "Semantic Vector Tools" is available here.
- A very simple text analyzer, TAR (Topic-Attribute Relationships), that tries to extract topics and related attributes based on paragraphs of texts. The number of time attributes are assigned to a topic are counted, at most once per paragraph.