• No results found

A neural generative model for joint learning topics and topic-specific word embeddings

N/A
N/A
Protected

Academic year: 2021

Share "A neural generative model for joint learning topics and topic-specific word embeddings"

Copied!
15
0
0

Loading.... (view fulltext now)

Full text

Loading

Figure

Figure 1: The Variational Auto-Encoder framework for the Joint Topic Word-embedding (JTW) model
Table 1: Spearman rank correlation coefficient on 7 benchmarks.
Figure 2: Topic coherence scores versus number of topics.
Table 3: Example topics discovered by JTW and MMSG, each topic is represented by the top 10 words sorted by their likelihoods
+2

References

Related documents

Straipsnyje nagrinėjamos teorinės inovatyvumo ir bibliotekų projektinės veiklos sąsajos, praktiškai at- liktu tyrimu pristatoma paslaugų, sukurtų Šiaulių rajono

The A23.3 design standard (CSA, 2014) presents a simplified method for computing the long-term deflection by applying a multiplier, that is a function of the sustained

Fig.. High usage profiles would allow an aircraft planning an emergency landing to recognize and avoid this populated area despite a soccer field normally holding promise as

One of my goals for Shaman Johnny’s Pop-Up Shop & Gallery was to create this same sense of communitas through the experience of meeting and spending time with Shaman Johnny.

Rodriguez-Lopez, “Existence and approximation of solutions for nonlinear function di ff erential equations with periodic boundary value conditions,” Journal of Computational and

Brief Description of Project: Develop and share an implementation plan for electronic medical record development but that will be sustainable for continued growth as we

We found that while most texts contain a relatively complete description of magnetism and its relation to cur- rent-carrying wires, few devote much space to the development of

The RMS Personnel Policy sets forth policies covering a full range of human resources topics including: resident responsibilities, salary, benefits for residents/fellows