PLSA (Probabilistic Latent Semantic Analysis) & Dialog Systems


Probabilistic Latent Semantic Analysis

See also:

Grammatico-Semantic Analysis | Latent Semantic & Dialog Systems 2011 | LSA (Latent Semantic Analysis) & Dialog Systems | LSI (Latent Semantic Indexing) & Dialog Systems | LSM (Latent Semantic Mapping) | MultiNet (Multilayered Extended Semantic Networks) | Question Semantic Representation (QSR) | Semantic Grammars & Dialog Systems | Semantic Networks & Dialog Systems | Semantic Tags & Dialog Systems | Semantic Web Reasoning | SemanticQA


Opinion mining and sentiment analysis [PDF] from iitb.ac.in B Pang… – Foundations and Trends in Information Retrieval, 2008 – dl.acm.org … NJ, 1992. 122. R. Higashinaka, M. Walker, and R. Prasad, “Learning to generate naturalistic utterances using reviews in spoken dialogue systems,” ACM Transactions on Speech and Language Processing (TSLP), 2007. 123. P … Cited by 957 – Related articles – Library Search – All 33 versions

Interactional Style Detection for Versatile Dialogue Response Using Prosodic and Semantic Features WB Liang, CH Wu, CH Wang… – … Annual Conference of the …, 2011 – isca-speech.org … Spoken dialogue systems have been applied to a wide range of domains, from simple goal-oriented applications such as airline travel … LDA extends the probabilistic latent semantic analysis, or simply PLSA, by treating the latent topic of each document as a random variable. … Related articles – All 2 versions

Building effective question answering characters [PDF] from upenn.edu A Leuski, R Patel, D Traum… – Proceedings of the 7th SIGdial …, 2009 – dl.acm.org … There are two sources of uncertainty in a spoken dialog system: the first is the complex nature of natural language (including ambigu- ity, vagueness, underspecification, indirect speech acts, etc.), making it difficult to compactly char … 1999. Probabilistic latent semantic index- ing. … Cited by 48 – Related articles – All 29 versions

A two-dimensional topic-aspect model for discovering multi-faceted topics [PDF] from uiuc.edu M Paul… – Urbana, 2010 – aaai.org … Probabilistic latent semantic indexing (PLSI) (Hofmann 1999) is a probabilistic model where each word w is associ- ated with a hidden variable z that represents the topic that the word belongs to. … The CL aspect focuses on dialogue systems, with words like dialogue and user. … Cited by 12 – Related articles – All 6 versions

A question-and-answer classification technique for constructing and managing spoken dialog system R Inoue, Y Kurosawa, K Mera… – Speech Database and …, 2011 – ieeexplore.ieee.org … There are various spoken dialog systems in our daily life such as those for car navigation and for providing sightseeing information [1][2][3][4][5]. They … To solve this problem, we classify the entries of the database using the probabilistic Latent Semantic Analysis method (pLSA). … Cited by 2 – Related articles

Semantic analysis and organization of spoken documents based on parameters derived from latent topics SY Kong… – Audio, Speech, and Language Processing, …, 2011 – ieeexplore.ieee.org … Probabilistic latent semantic analysis is used as a typical example approach for unsupervised topic analysis in most ex- periments, although latent Dirichlet allocation is also used in some experiments to show that the proposed measures are equally applicable for different … Cited by 2 – Related articles – All 3 versions

A statistical approach for text processing in virtual humans [PDF] from dtic.mil A Leuski… – 2008 – DTIC Document … Other approaches include Probabilistic Latent Semantic Indexing (PLSI) (Hofmann, 1999) and Latent Dirichlet Allocation (LDA) (Blei et al., 2003), where the authors model text collections by a finite set of … Mak- ing grammar-based generation easier to deploy in dialogue systems. … Cited by 22 – Related articles – Library Search – All 17 versions

[PDF] Learning user intentions in spoken dialogue systems [PDF] from ulaval.ca HR Chinaei, B Chaib-draa… – ICAART, 2009 – damas.ift.ulaval.ca Page 1. LEARNING USER INTENTIONS IN SPOKEN DIALOGUE SYSTEMS Hamid … Keywords: Learning, Spoken Dialogue Systems Abstract: A common problem in spoken dialogue systems is finding the intention of the user. This … Cited by 3 – Related articles – View as HTML – All 5 versions

Grounding of Word Meanings in Latent Dirichlet Allocation-Based Multimodal Concepts [PDF] from nict.go.jp T Nakamura, T Araki, T Nagai… – Advanced Robotics, 2011 – ingentaconnect.com … In Ref. [9], we have proposed multi- modal categorization that is based on probabilistic latent semantic analysis (pLSA) [10]. The multimodal categorization has been shown to be successful for categoriz- ing objects in the same way as humans do without any supervision. … Related articles – All 2 versions

Automatic lecture transcription by exploiting presentation slide information for language model adaptation [PDF] from kyoto-u.ac.jp T Kawahara, Y Nemoto… – Acoustics, Speech and …, 2008 – ieeexplore.ieee.org … ICSLP, volume 1, pages 162-165, 2000. [8] T.Hoffman. Probabilistic latent semantic indexing. In Proc. SIG-IR, 1999. … [13] T.Misu and T.Kawahara. A bootstrapping approach for devel- oping language model of new spoken dialogue systems by se- lecting web texts. In Proc. … Cited by 13 – Related articles – All 7 versions

Application of Hidden Topic Markov Models on Spoken Dialogue Systems HR Chinaei, B Chaib-draa… – Agents and Artificial …, 2010 – Springer … In: Artificial Intelli- gence and Statistics (AISTATS 2007), San Juan, Puerto Rico (2007) 7. Hofmann, T.: Probabilistic latent semantic analysis. … 512-521 (1999) Page 13. Application of Hidden Topic Markov Models on Spoken Dialogue Systems 163 10. … Related articles – All 2 versions

An efficient hybrid music recommender system using an incrementally trainable probabilistic generative model [PDF] from aist.go.jp K Yoshii, M Goto, K Komatani… – Audio, Speech, and …, 2008 – ieeexplore.ieee.org … To estimate , Hofmann and Puzicha [14] used a probabilistic generative model called an aspect model. A data mining technique based on the aspect model is known as the probabilistic latent semantic analysis (pLSA) [15]. The … Cited by 39 – Related articles – BL Direct – All 15 versions

Psychomime Classification and Visualization Using a Self-Organizing Map for Implementing Emotional Spoken Dialogue System Y Kurosawa, K Mera… – Spoken Dialogue Systems …, 2011 – Springer … USING A SELF-ORGANIZING MAP FOR IMPLEMENTING EMOTIONAL SPOKEN DIALOGUE SYSTEM … W. Minker et al. (eds.), Spoken Dialogue Systems Technology and Design, DOI 10.1007/978-1-4419-7934-6_5, (c) Springer Science+Business Media, LLC 2011 However, … Related articles

Language models learning for domain-specific natural language user interaction S Bai, CL Huang, YK Tan… – Robotics and Biomimetics ( …, 2009 – ieeexplore.ieee.org … topic modeling technologies. The proposed algorithm first performs topic decomposition (TD) on the combined dataset of domain-specific and general-domain data using probabilistic latent semantic analysis (PLSA). Then it … Related articles – All 2 versions

Topic tracking language model for speech recognition S Watanabe, T Iwata, T Hori, A Sako… – Computer Speech & …, 2011 – Elsevier … Volume 25, Issue 2, April 2011, Pages 440-461 Language and speech issues in the engineering of companionable dialogue systems. … are obtained by clustering articles (Iyer and Ostendorf, 1996) or by applying the well-known (Probabilistic) Latent Semantic Analysis (LSA … Cited by 5 – Related articles – All 3 versions

Off-Topic Detection in Automated Speech Assessment Applications J Cheng… – Twelfth Annual Conference of the International …, 2011 – isca-speech.org … of spoken dialog system. Higgins et al. [6] used the similarity of vocabulary items between new essays and sample on-topic essays (or prompts) to identify those that were off-topic. … 391-407, 1990. [3] T. Hofmann, “Probabilistic latent semantic indexing,” in SIGIR99, pp. 50-57. … Cited by 1 – Related articles – All 2 versions

[PDF] Learning the Reward Model of Dialogue POMDPs from Data [PDF] from psu.edu A Boularias, HR Chinaei… – NIPS Workshop on Machine …, 2010 – Citeseer … uncertainty characterizing dialogues, there has been interest for modelling the dialogue man- ager of spoken dialogue systems using Partially … observations in Markovian domains such as part-of-speech tagging [3]. In LDA, similar to Probabilistic Latent Semantic Analysis (PLSA … Cited by 1 – Related articles – View as HTML – All 4 versions

Topic segmentation [PDF] from psu.edu M Purver – Spoken Language Understanding, 2011 – Wiley Online Library … Clearly, this is only a useful task when applied to recordings of some length – short segments of speech such as an utterance in a typical spoken dialogue system tend already to be topically homogeneous and thus not to require segmentation. … Cited by 3 – Related articles – All 5 versions

[PDF] Cross-collection topic models: Automatically comparing and contrasting text [PDF] from jhu.edu M Paul – Urbana, 2009 – cs.jhu.edu … Our model improves over ccMix by replacing their probabilistic latent semantic indexing (pLSI) (Hofmann, 1999) framework with that of LDA … We see that in CL, this is strongly relevant to dialogue systems; in linguistics, this topic is more focused on human behavior and social inter … Cited by 2 – Related articles – View as HTML – All 2 versions

Voice-based information retrieval-how far are we from the text-based information retrieval? [PDF] from ntu.edu.tw L Lee… – … & Understanding, 2009. ASRU 2009. IEEE …, 2009 – ieeexplore.ieee.org Page 1. Voice-based Information Retrieval – how far are we from the text-based information retrieval ? Lin-shan Lee and Yi-cheng Pan National Taiwan University Taipei, Taiwan, ROC lslee@gate.sinica.edu.tw thomashughPan@gmail.com … Cited by 1 – Related articles – All 5 versions

PLSA-based topic detection in meetings for adaptation of lexicon and language model [PDF] from kyoto-u.ac.jp Y Akita, Y Nemoto… – Eighth Annual Conference of the …, 2007 – isca-speech.org … ICSLP, 2004. [10] T. Hofmann, “Probabilistic Latent Semantic Indexing,” in Proc. SIG-IR, 1999. … ICASSP, 2005. [13] T. Misu and T. Kawahara, “A Bootstrapping Approach for Developing Language Model of New Spoken Dialogue Systems by Selecting Web Texts,” in Proc. … Cited by 9 – Related articles – All 4 versions

Type-ii dialogue systems for information access from unstructured knowledge sources [PDF] from psu.edu Y Pan… – … & Understanding, 2007. ASRU. IEEE Workshop …, 2007 – ieeexplore.ieee.org Page 1. TYPE-II DIALOGUE SYSTEMS FOR INFORMATION ACCESS FROM UNSTRUCTURED KNOWLEDGE SOURCES Yi-cheng Pan and Lin-shan Lee … Typical example tasks of this type of dialogue systems include retrieval, browsing and question answering. … Cited by 6 – Related articles – All 8 versions

Statistical language model adaptation: review and perspectives [PDF] from psu.edu JR Bellegarda – Speech communication, 2004 – Elsevier … This is often the case, for example, of a typical dialog state in a dialog system. … Alternatively, in the course of deploying dialog systems, it is customary to conduct “wizard of Oz” experiments to fine tune certain dialog states (cf. … Cited by 139 – Related articles – All 8 versions

Biron, what’s the topic? a multi-modal topic tracker for improved human-robot interaction [PDF] from uni-bielefeld.de JF Maas, T Spexard, J Fritsch… – Robot and Human …, 2006 – ieeexplore.ieee.org … In combination with the dialogue system, the gesture- and object recognition modules deliver information about objects referred to by … Fuzzy Se- mantics [28] and Latent Semantic Analysis (LSA) [8]. We did not implement the popular Probabilistic Latent Semantic Analysis (PLSA … Cited by 17 – Related articles – All 6 versions

Latent Variable Models for Causal Knowledge Acquisition T Inui, H Takamura… – Computational Linguistics and …, 2007 – Springer … sense knowledge base. For example, in question-answering systems [9] and dialogue systems [1], acquiring a great deal of knowledge about causal relations or causality between events is one central issue. The causal relations … Cited by 1 – Related articles – BL Direct – All 7 versions

Multi-layered summarization of spoken document archives by information extraction and semantic structuring [PDF] from pitt.edu L Lee, S Kong, Y Pan, Y Fu… – … Conference on Spoken …, 2006 – isca-speech.org … H. Li, M.-H. Lee, B. Chen, and L.-S. Lee, “Hierarchical topic organization and visual presentation of spoken documents using probabilistic latent semantic analysis (plsa … C., T.-H. Lee, Y.-S. Lee, Y.-S. Fu, Y.-T. Huang, and L.-S. Lee, “A multi-modal dialogue system for information … Cited by 8 – Related articles – All 5 versions

Meeting decision detection: multimodal information fusion for multi-party dialogue understanding [PDF] from ed.ac.uk PY Hsueh – 2009 – era.lib.ed.ac.uk Page 1. Meeting Decision Detection: Multimodal Information Fusion for Multi-Party Dialogue Understanding Pei-Yun Sabrina Hsueh T H E U NIVER S I T Y O F E DI NBU R G H Doctor of Philosophy Institute for Communicating and Collaborative Systems School of Informatics … Cited by 1 – Related articles – All 2 versions

Latent prosody analysis for robust speaker identification YF Liao, ZH Chen… – Audio, Speech, and Language …, 2007 – ieeexplore.ieee.org … only unseen handsets. Index Terms-Latent prosody analysis, latent semantic analysis, probabilistic latent semantic analysis, speaker identification, speaker recognition, speech prosody. I. INTRODUCTION HANDSETS that … Cited by 2 – Related articles – BL Direct – All 6 versions

Resolving Direct and Indirect Anaphora for Japanese Definite Noun Phrases [PDF] from tohoku.ac.jp N Inoue, R Iida, K Inui… – Information and Media …, 2010 – J-STAGE Page 1. Information and Media Technologies 5(1): 295-320 (2010) reprinted from: Journal of Natural Language Processing 17(1): 221-246 (2010) (c) The Association for Natural Language Processing 295 Resolving Direct and Indirect Anaphora for Japanese … Related articles – All 9 versions

Efficient interactive retrieval of spoken documents with key terms ranked by reinforcement learning [PDF] from pitt.edu Y Pan, J Chen, Y Lee, Y Fu… – … International Conference on …, 2006 – isca-speech.org … [3] Marilyn A. Walker, “An application of reinforcement learning to dialogue strategy selection in a spoken dialogue system for email,” Journal of Artificial Intelligence Research 12, pp. … [7] Thomas Hofmann, “Probabilistic latent semantic indexing,” in SIGIR, 1999, pp. 50-57. … Cited by 5 – Related articles – All 5 versions

LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION FOR MANDARIN CHINESE: PRINCIPLES, APPLICATION TASKS AND PROTOTYPE EXAMPLES L Lee – Advances in Chinese spoken language processing, 2007 – books.google.com … 64 All three parts are based on a very useful semantic analysis framework for spoken documents, the Probabilistic Latent Semantic Analysis (PLSA). Below, these three parts are very briefly introduced first, followed by a summary of the functionalities of the system. 6.1. … Related articles

Intelligent Transcription System Based on Spontaneous Speech Processing [PDF] from kyoto-u.ac.jp T Kawahara – … of Knowledge Society Infrastructure, 2007. ICKS …, 2007 – ieeexplore.ieee.org … IEEE-ICASSP, volume 1, pages 689-692, 2005. [15] T.Misu and T.Kawahara. A bootstrapping approach for developing language model of new spoken dialogue systems by selecting web texts. In Proc. … [20] T.Hoffman. Probabilistic latent semantic indexing. In Proc. SIG-IR, 1999. … Related articles – All 5 versions

[PDF] Third International Joint Conference on Natural Language Processing [PDF] from mercubuana.ac.id L Host – 2008 – pascasarjana.mercubuana.ac.id … Generic Text Summarization Using Probabilistic Latent Semantic Indexing Harendra Bhandari, Masashi Shimbo, Takahiko Ito and Yuji … Rapid Prototyping of Robust Language Understanding Modules for Spoken Dialogue Systems Yuichiro Fukubayashi, Kazunori Komatani … View as HTML – All 9 versions

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge [PDF] from kuleuven.be B Schuller, A Batliner, S Steidl… – Speech Communication, 2011 – Elsevier … NMF, a method strictly related to probabilistic latent semantic analysis [79], is a recent alternative to PCA in which the data and components are assumed to be non-negative: NMF learns to represent emotional classes with a set of basic emotional 10 subclasses. … Cited by 32 – Related articles – All 9 versions

Simulation analysis for interactive retrieval of spoken documents with key terms ranked by reinforcement learning [PDF] from pitt.edu Y Pan… – Spoken Language Technology Workshop, 2006 …, 2006 – ieeexplore.ieee.org … Hsieh, T.-H Lee, Y.-S Lee, Y.-S Fu, Y.-T Huang, and L.-S Lee, “A multi-modal dialogue system for information … Yu tsun Huang, Chien chih Wang, and Lin shan Lee, “Improved spoken document retrieval with dynamic key term lexicon and probabilistic latent semantic analysis (plsa … Cited by 2 – Related articles – All 6 versions

[PDF] Language model adaptation based on PLSA of topics and speakers for automatic transcription of panel discussions [PDF] from psu.edu Y Akita… – IEICE transactions on information and systems, 2005 – Citeseer … Speech Audio Process., vol.12, no.4, pp.391-400, 2004. [9] T. Hofmann, “Probabilistic latent semantic indexing,” Proc. SIG-IR, pp.50-57, 1999. … He has published more than 100 technical papers covering speech recognition, confidence measures, and spoken dialogue systems. … Cited by 11 – Related articles – View as HTML – BL Direct – All 10 versions

Ontological technologies for user modelling [PDF] from pitt.edu S Sosnovsky… – International Journal of Metadata, …, 2010 – Inderscience … To elicit individual user models, intelligent dialog systems of the early user modelling age usually followed one of two ways: they either attempted to ask the user a fishing question, or utilised rules, predicate logic and other … (2005) used probabilistic latent semantic analysis to … Cited by 6 – Related articles – All 11 versions

Language modeling approaches to question answering [PDF] from drexel.edu P Banerjee – 2009 – dspace.library.drexel.edu … 30 Figure 4: A Conceptual Model of Probabilistic Latent Semantic Analysis and the Aspect Model ….. 44 … aspect as defined by Probabilistic Latent Semantic Analysis) to a question. We then use … Cited by 1 – Related articles – Library Search – All 11 versions

Machine Learning for Categorization of Speech Utterances [PDF] from sinaidiagnostics.com A Albalate, D Suendermann… – … Analysis of Evolution …, 2006 – Wiley Online Library … As a result of accelerated technological development and, particularly, due to the progressive advances in the field of automated speech recognition, first Spoken Language Dialog Systems (SLDSs) emerged in the mid 1990s as a new, important form of human-machine … Related articles – All 11 versions

A Multi-layered Summarization System for Multi-media Archives by Understanding and Structuring of Chinese Spoken Documents L Lee, S Kong, Y Pan, Y Fu, Y Huang… – Chinese Spoken …, 2006 – Springer … H. Li, M.-H. Lee, B. Chen, and L.-S. Lee, “Hierarchical topic organization and visual presentation of spoken documents using probabilistic latent semantic analysis (plsa … C., T.-H. Lee, Y.-S. Lee, Y.-S. Fu, Y.-T. Huang, and L.-S. Lee, “A multi-modal dialogue system for information … Related articles – BL Direct – All 2 versions

Spoken document understanding and organization [PDF] from ntu.edu.tw L Lee… – Signal Processing Magazine, IEEE, 2005 – ieeexplore.ieee.org Page 1. (c) ARTVILLE & COMSTOCK IEEE SIGNAL PROCESSING MAGAZINE [42] SEPTEMBER 2005 1053-5888/05/$20.00(c)2005IEEE [Lin-shan Lee and Berlin Chen] Speech is the primary and most convenient means of … Cited by 74 – Related articles – BL Direct – All 4 versions

Web user clustering and Web prefetching using Random Indexing with weight functions M Wan, A Jönsson, C Wang, L Li… – Knowledge and Information …, 2011 – Springer Page 1. Knowl Inf Syst DOI 10.1007/s10115-011-0453-x REGULAR PAPER Web user clustering and Web prefetching using Random Indexing with weight functions Miao Wan · Arne Jönsson · Cong Wang · Lixiang Li · Yixian Yang … Cited by 1 – Related articles

User model interoperability: a survey [PDF] from unito.it F Carmagnola, F Cena… – User Modeling and User-Adapted …, 2011 – Springer Page 1. User Model User-Adap Inter (2011) 21:285-331 DOI 10.1007/s11257-011- 9097-5 ORIGINAL PAPER User model interoperability: a survey Francesca Carmagnola · Federica Cena · Cristina Gena Received: 12 May … Cited by 5 – Related articles – All 8 versions

Human-level performance on word analogy questions by latent relational analysis [PDF] from nrc-cnrc.gc.ca P Turney – 2004 – nparc.cisti-icist.nrc-cnrc.gc.ca … How can I kill a process? • How can I get into the LISP interpreter? • Tell me how to get out of Emacs. Human-computer dialogue systems are currently limited to very simple, literal language. We believe that the task of mapping … Cited by 5 – Related articles – All 11 versions

Latent semantic language modeling for speech recognition JR Bellegarda – Mathematical foundations of speech and language …, 2004 – Springer Page 1. LATENT SEMANTIC LANGUAGE MODELING FOR SPEECH RECOGNITION JEROME R. BELLEGARDA’ Abstract. Statistical language models used in large vocabulary speech recognition must properly capture the … Cited by 1 – Related articles – BL Direct – All 3 versions

Identifying semantic relations in text D Gildea… – Exploring artificial intelligence in the new …, 2003 – dl.acm.org … 29-May 04, 2000, Seattle, Washington. 4. Bobrow, DG, RM Kaplan, M. Kay, DA Norman, H. Thompson, and T. Winograd (1977). GUS, A frame driven dialog system. Artificial Intelligence 8, 155-173. 5. Peter F. Brown , John Cocke … Cited by 2 – Related articles – All 2 versions

Audio content analysis JJ Burred, M Haller, S Jin, A Samour… – Semantic Multimedia and …, 2008 – Springer Page 1. Chapter 5 Audio Content Analysis Juan José Burred, Martin Haller, Shan Jin, Amjad Samour, and Thomas Sikora 5.1 Introduction Since the introduction of digital audio more than 30 years ago, computers and signal … Cited by 1 – Related articles – All 4 versions

[PDF] Robust Speaker Identification System [PDF] from iisc.ernet.in S Patra – 2007 – serc.iisc.ernet.in … etc. With speaker recogni- tion technologies, the intelligent answering machines can be implemented with personalized caller greetings, even personalized dialog systems can be built which can recognize the user, greet to … Related articles – View as HTML

[HTML] A Thematic Bibliography on Dialogue Processing [HTML] from unige.ch A Popescu-Belis, A Clark, M Georgescul… – 2003 – issco.unige.ch … 3.1. Dialogue modelling and theories of dialogue. 3.2. Discourse structure and analysis, language modelling. 3.3. Dialogue systems and meeting-related applications. 3.3.1. Human-computer dialogue and its evaluation. 3.3.2. Meeting browsers. 3.4. Dialogue data and annotation … Cited by 1 – Related articles – Cached – All 2 versions

Natural Language Understanding DGD Jurafsky – Exploring Artificial Intelligence in the New …, 2003 – books.google.com … (4)[TRAVEL1 want to gl [ORiGiNfrom Denver][DESTINATION to Boston] on Such dialogue systems have a frame, or template … Our shallow semantic level of interpretation can be used for many purposes besides generalizing information extraction and semantic dialogue systems. … Related articles – All 2 versions

Apple Computer, Inc. JR Bellegarda – Pattern recognition in speech and language …, 2003 – books.google.com Page 270. 9 Statistical Language Models With Embedded Latent Semantic Knowledge Jerome R. Bellegarda Apple Computer, Inc. 9.1 Introduction The Bayesian approach pervasive in today’s speech recognition systems entails … Related articles

Useful transcriptions of webcast lectures [PDF] from 142.150.190.46 C Munteanu – 2009 – 142.150.190.46 … domains appear due to advances in both areas. One particular example is the domain of natural-language-based dialog systems [Bernsen et al., 1998], a research area that emerged more than 20 years ago, and one in which HCI and ASR/NLP research must work together. … Related articles – Library Search – All 9 versions

A framework for exploiting electronic documentation in support of innovation processes [TXT] from sun.ac.za JW Uys – 2010 – scholar.sun.ac.za … Appendix B – Topic Modelling Techniques XV 16.1 Unigram Model XV 16.2 Mixture of Unigrams Model XVI 16.3 Probabilistic Latent Semantic Indexing (pLSI) XVIII 16.4 Latent Dirichlet Allocation (LDA) XIX 16.5 Author-Topic Model XXII 16.6 Hierarchical Latent Dirichlet … Cited by 3 – Related articles – All 6 versions