Results 61 to 70 of about 3,238,976 (181)

An Automatic Approach for Document-level Topic Model Evaluation

, 2017
Topic models jointly learn topics and document-level topic distribution. Extrinsic evaluation of topic models tends to focus exclusively on topic-level evaluation, e.g. by assessing the coherence of topics.
Baldwin, Timothy, Bhatia, Shraey, Lau, Jey Han   +2 more
core   +1 more source

Ideology from topic mixture statistics: inference method and example application to carbon tax public opinion

Environmental Data Science
Political opposition to fiscal climate policy, such as a carbon tax, typically appeals to fiscal conservative ideology. Here, we ask to what extent public opposition to the carbon tax in Canada is, in fact, ideological in origin.
Maximilian Puelma Touzel, Erick Lachapelle   +1 more
doaj   +1 more source

ToC-RWG: Explore the Combination of Topic Model and Citation Information for Automatic Related Work Generation

IEEE Access, 2020
Automatic related work generation is a new challenge in multi-document scientific summarization focusing on refining a related work section for a given scientific paper.
Pancheng Wang, Shasha Li, Haifang Zhou, Jintao Tang, Ting Wang   +4 more
doaj   +1 more source

Automatically extracting polarity-bearing topics for cross-domain sentiment classification [PDF]

, 2011
Joint sentiment-topic (JST) model was previously proposed to detect sentiment and topic simultaneously from text. The only supervision required by JST model learning is domain-independent polarity word priors.
Alani, Harith, He, Yulan, Lin, Chenghua
core   +1 more source

A Method for Extending Ontologies with Application to the Materials Science Domain

Data Science Journal, 2019
In the materials science domain the data-driven science paradigm has become the focus since the beginning of the 2000s. A large number of research groups and communities are building and developing data-driven workflows.
Huanyu Li, Rickard Armiento, Patrick Lambrix   +2 more
doaj   +1 more source

Topic Modeling

Im KONDE-Projekt, das aus Hochschulraumstrukturmitteln finanziert wird, beschäftigten sich sieben universitäre Partner und drei weitere Einrichtungen aus unterschiedlichen Blickwinkeln mit theoretischen und praktischen Aspekten der Digitalen Edition. Ein Outcome des Projektes stellt das Weißbuch dar, welches über 200 Artikel zum Thema Digitale Edition ...
Yanghui Rao, Qing Li
  +5 more sources

How Effective Is the Judiciary? Evidence on Correlation Between Cases’ Characteristics and Probability of Appeal

European Journal of Empirical Legal Studies
This research proposes a way to assess judicial effectiveness, proxied by the probability of appeal of a decision. Focusing on the example of regional courts in Poland, it classifies cases based on their most accurate topic, creating a topic model on ...
Maciej Świtała
doaj   +1 more source

Empirical Comparison of Word Similarity Measures Based on Co-Occurrence, Context, and a Vector Space Model

Journal of Information Science Theory and Practice, 2020
Word similarity is often measured to enhance system performance in the information retrieval field and other related areas. This paper reports on an experimental comparison of values for word similarity measures that were computed based on 50 ...
Natsuki Kadowaki, Kazuaki Kishida
doaj   +1 more source

Cross-Domain Explainable Recommendation Using Graph Convolutional Networks and a Topic Model

IEEE Access
Graph Convolutional Network (GCN)-based recommendation systems (RSs) have recently gained popularity for their ability to improve recommendation accuracy by utilizing neighborhood information in user-item interaction graphs.
Kunyoung Kim, Mye Sohn, Jongmo Kim
doaj   +1 more source

TCMHG: Topic-Based Cross-Modal Hypergraph Learning for Online Service Recommendations

IEEE Access, 2018
Online product reviews sentiment classification plays an important role on service recommendation, yet most of current researches on it only focus on single-modal information ignoring the complementary information, that results in unsatisfied accuracy of
Zhikui Chen, Fei Lu, Xu Yuan, Fangming Zhong   +3 more
doaj   +1 more source