Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dialogue Session Segmentation by Embedding-Enhanced TextTiling   In human-computer conversation systems, the context of a user-issued
utterance is particularly important because it provides useful background
information of the conversation. However, it is unwise to track all previous
utterances in the current session as not all of them are equally important. In
this paper, we address the problem of session segmentation. We propose an
embedding-enhanced TextTiling approach, inspired by the observation that
conversation utterances are highly noisy, and that word embeddings provide a
robust way of capturing semantics. Experimental results show that our approach
achieves better performance than the TextTiling, MMD approaches.

11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg