S2vNTM: Semi-supervised vMF Neural Topic Modeling

Language model based methods are powerful techniques for text classification. However, the models have several shortcomings. (1) It is difficult to integrate human knowledge such as keywords. (2) It needs a lot of resources to train the models. (3) It relied on large text data to pretrain. In this paper, we propose Semi-Supervised vMF Neural Topic Modeling (S2vNTM) to overcome these difficulties. S2vNTM takes a few seed keywords as input for topics. S2vNTM leverages the pattern of keywords to identify potential topics, as well as optimize the quality of topics' keywords sets. Across a variety of datasets, S2vNTM outperforms existing semi-supervised topic modeling methods in classification accuracy with limited keywords provided. S2vNTM is at least twice as fast as baselines.Comment: 17 pages, 9 figures, ICLR Workshop 2023. arXiv admin note: text overlap with arXiv:2307.0122

vONTSS: vMF based semi-supervised neural topic modeling with optimal transport

Recently, Neural Topic Models (NTM), inspired by variational autoencoders, have attracted a lot of research interest; however, these methods have limited applications in the real world due to the challenge of incorporating human knowledge. This work presents a semi-supervised neural topic modeling method, vONTSS, which uses von Mises-Fisher (vMF) based variational autoencoders and optimal transport. When a few keywords per topic are provided, vONTSS in the semi-supervised setting generates potential topics and optimizes topic-keyword quality and topic classification. Experiments show that vONTSS outperforms existing semi-supervised topic modeling methods in classification accuracy and diversity. vONTSS also supports unsupervised topic modeling. Quantitative and qualitative experiments show that vONTSS in the unsupervised setting outperforms recent NTMs on multiple aspects: vONTSS discovers highly clustered and coherent topics on benchmark datasets. It is also much faster than the state-of-the-art weakly supervised text classification method while achieving similar classification performance. We further prove the equivalence of optimal transport loss and cross-entropy loss at the global minimum.Comment: 24 pages, 12 figures, ACL findings 202

Project Report: PLAiR Market Research Log

Our development process of the PLAiR Dongle marketing plan is presented in this marketing log. In order to develop the marketing log, we incorporated the knowledge from the text book. The report begins with the idea generation concept which provides a basis of how to select a product for a team project. Secondly, we conducted a thorough research to understand in detail about our product, and our competitors. We, then interviewed people and used the reports available in PSU’s library of databases and business journals(Mintel, Euromonitor, etc.) to find out what the customer/market needs are and to understand whether our product had the correct value proposition to fit in that market. Based on our research we found our target market and tailor made a marketing plan for our target market. From the class lectures, the knowledge from marketing books, guidance from the instructor, interviews and an extensive literature review we developed the product plan, and the 4P strategies. To be beneficial for advancing future research, we added key learning and suggestion for each step in developing the plan for the PLAiR

Project Report: PLAiR Marketing Plan

With traditional TV and the internet merging faster than ever before, more and more people are using mobile devices, including cell phones, tablets and laptops, to watch streamed content online. The need for connecting these mobile devices to bigger screens, TVs, is forming a considerable market for the streaming-to-TV devices. PLAiR is a Wi-Fi enabled HDMI dongle which enables a mobile device user to beam the content to the TV screen through a HDMI interface. PLAiR is the only device in the market which does not restrict the users to a particular device or a particular operating system since it is designed to work with any type of device regardless of the OS. This marketing plan proposes to explore the potential market for the PLAiR. The report evaluates the overall market size and then identifies target market and potential customer segments. The plan further analyzes customers’ value drivers and their compelling reasons to act. Additionally, the plan provides a brief competitor analysis to gauge the competitive environment. The plan concludes by proposing strategies related to the positioning, distribution, promotion and pricing of PLAiR