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Book part
Publication date: 13 March 2023

Jochen Hartmann and Oded Netzer

The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing…

Abstract

The increasing importance and proliferation of text data provide a unique opportunity and novel lens to study human communication across a myriad of business and marketing applications. For example, consumers compare and review products online, individuals interact with their voice assistants to search, shop, and express their needs, investors seek to extract signals from firms' press releases to improve their investment decisions, and firms analyze sales call transcripts to increase customer satisfaction and conversions. However, extracting meaningful information from unstructured text data is a nontrivial task. In this chapter, we review established natural language processing (NLP) methods for traditional tasks (e.g., LDA for topic modeling and lexicons for sentiment analysis and writing style extraction) and provide an outlook into the future of NLP in marketing, covering recent embedding-based approaches, pretrained language models, and transfer learning for novel tasks such as automated text generation and multi-modal representation learning. These emerging approaches allow the field to improve its ability to perform certain tasks that we have been using for more than a decade (e.g., text classification). But more importantly, they unlock entirely new types of tasks that bring about novel research opportunities (e.g., text summarization, and generative question answering). We conclude with a roadmap and research agenda for promising NLP applications in marketing and provide supplementary code examples to help interested scholars to explore opportunities related to NLP in marketing.

Article
Publication date: 8 May 2018

Nabila Ahmed Khodeir, Hanan Elazhary and Nayer Wanas

The purpose of this paper is to present an algorithm to generate story problems via controlled parameters in the domain of mathematics. The generation process is performed in the…

Abstract

Purpose

The purpose of this paper is to present an algorithm to generate story problems via controlled parameters in the domain of mathematics. The generation process is performed in the problem generation module in the context of an intelligent tutoring system suggested in this paper. Controlling the question parameters allows for adapting the generated questions according to the specific student needs. Story problems are selected since they are one of the most important types of problems in mathematics, as they help train students to apply their knowledge to real-world problems. Such problems target improving different student’s skills including literacy skills through reading the problem, recognizing the embedded mathematical information, and applying the required arithmetic operators.

Design/methodology/approach

Natural language generation (NLG) techniques are used to control the difficulty level of the generated story problem header in addition to effecting variations from the natural language point of view. The proposed NLG technique is based on different separated knowledge categories to provide flexibility in the generation process and allow porting the module to other contexts, domains, and to other natural languages without a complete redesign.

Findings

The approach has been empirically evaluated, and the results show that the generated problems are sound, clear, and naturally readable. This is in addition to the usability of the tutoring system itself.

Research limitations/implications

The generation technique is confined to the problem described using rhetorical schemas. Nevertheless, it can generate any problem provided that the rhetorical schema is available.

Originality/value

Most story problems generation systems limit the variation of the story problems to formulating the sentences that describe the story problem and the associated mathematical operations. In contrast, this paper presents a story problems generation technique that allows variations in the structure of the narrative story as well as the context, sentences, wordings, and mathematical operations. This variability allows assessing different student skills along different dimensions with gradually increasing difficulty levels.

Details

The International Journal of Information and Learning Technology, vol. 35 no. 3
Type: Research Article
ISSN: 2056-4880

Keywords

Article
Publication date: 1 April 1986

P J. DANIELS

Selected current and recent work in the area of cognitive modelling is reviewed. Particular attention is paid to user models (that is, the model held by a system of a user). The…

Abstract

Selected current and recent work in the area of cognitive modelling is reviewed. Particular attention is paid to user models (that is, the model held by a system of a user). The relevance of this work to information retrieval is assessed and some attempts to include user models in IR systems are discussed. Implications are drawn for future work in IR.

Details

Journal of Documentation, vol. 42 no. 4
Type: Research Article
ISSN: 0022-0418

Article
Publication date: 1 January 1984

H. FARRENY and H. PRADE

This paper deals with a problem encountered in natural language generation which seems to have been largely ignored in the literature, that of generating non‐ambiguous (i.e…

Abstract

This paper deals with a problem encountered in natural language generation which seems to have been largely ignored in the literature, that of generating non‐ambiguous (i.e. discriminating) designations of objects in a given context, from a knowledge basis, which associates the properties and relations, concerning the objects present in the environment, with their respective formal labels. A search algorithm of type A is proposed, which always generates a discriminating designation when such a designation exists in terms of the available knowledge; for the evaluation the algorithm uses a subjective length function which takes into account the “intelligibility” of the designation. This work takes place in the SYROCO system, a dialogue interface for limited domains of discourse; the sentence interpretation as well as the sentence generation in SYROCO are briefly presented in the first part of this paper.

Details

Kybernetes, vol. 13 no. 1
Type: Research Article
ISSN: 0368-492X

Book part
Publication date: 13 March 2023

David A. Schweidel, Martin Reisenbichler, Thomas Reutterer and Kunpeng Zhang

Advances in artificial intelligence have ushered in new opportunities for marketers in the domain of content generation. We discuss approaches that have emerged to generate text…

Abstract

Advances in artificial intelligence have ushered in new opportunities for marketers in the domain of content generation. We discuss approaches that have emerged to generate text and image content. Drawing on the customer equity framework, we then discuss the potential applications of automated content generation for customer acquisition, relationship development, and customer retention. We conclude by discussing important considerations that businesses must make prior to adopting automated content generation.

Article
Publication date: 1 March 1998

Robert Gaizauskas and Yorick Wilks

In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified…

1390

Abstract

In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining.

Details

Journal of Documentation, vol. 54 no. 1
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 1 October 2005

Hamish Cunningham, Kalina Bontcheva and Yaoyong Li

Seeks to explore the gap that exists between knowledge management (KM) systems and the natural language materials that form almost all corporate data stores.

2597

Abstract

Purpose

Seeks to explore the gap that exists between knowledge management (KM) systems and the natural language materials that form almost all corporate data stores.

Design/methodology/approach

A conceptual discussion and approach are taken using recent scientific results in the fields of the semantic web and ontology‐based information extraction.

Findings

Provides a high‐level introduction to information extraction (IE) and descriptions of application scenarios for KM tools that exploit IE, a form of natural language analysis to link semantic web models with documents. The paper presents some examples of ontology‐based IE systems, one of which, KIM, is under development in the SEKT Project. KIM offers IE‐based facilities for metadata creation, storage and conceptual search. The system can be used by diverse applications for annotating and querying documents.

Originality/value

Focuses on technologies and facilities that will become an important part of next‐generation KM applications.

Details

Journal of Knowledge Management, vol. 9 no. 5
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 1 October 2005

John Davies, Alistair Duke, Nick Kings, Dunja Mladenić, Kalina Bontcheva, Miha Grčar, Richard Benjamins, Jesus Contreras, Mercedes Blazquez Civico and Tim Glover

The paper shows how access to knowledge can be enhanced by using a set of innovative approaches and technologies based on the semantic web.

3069

Abstract

Purpose

The paper shows how access to knowledge can be enhanced by using a set of innovative approaches and technologies based on the semantic web.

Design/methodology/approach

Emerging trends in knowledge access are considered followed by a description of how ontologies and semantics can contribute. A set of tools is then presented which is based on semantic web technology. For each of these tools a detailed description of the approach is given together with an analysis of related and future work as appropriate.

Findings

The tools presented are at the prototype stage but can already show how knowledge access can be improved by allowing users to more precisely express what they are looking for and by presenting to them in a form that is appropriate to their current context.

Research limitations/implications

The tools show promising results in improving access to knowledge which will be further evaluated within a practical setting. The tools will be integrated and trialled as part of case studies within the SEKT project. This will allow their usability and practical applicability to be measured.

Practical implications

Ontologies as a form of knowledge representation are increasing in importance. Knowledge management, and in particular knowledge access, will benefit from their widespread acceptance. The use of open standards and compatible tools in this area will be important to support interoperability and widespread access to disparate knowledge repositories.

Originality/value

The paper presents research in an emerging but increasingly important field, i.e. semantic web‐based knowledge technology. It describes how this technology can satisfy the demand for improved knowledge access, including providing knowledge delivery to users at the right time and in the correct form.

Details

Journal of Knowledge Management, vol. 9 no. 5
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 17 June 2019

Jeannette Paschen, Jan Kietzmann and Tim Christian Kietzmann

The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this…

16136

Abstract

Purpose

The purpose of this paper is to explain the technological phenomenon artificial intelligence (AI) and how it can contribute to knowledge-based marketing in B2B. Specifically, this paper describes the foundational building blocks of any artificial intelligence system and their interrelationships. This paper also discusses the implications of the different building blocks with respect to market knowledge in B2B marketing and outlines avenues for future research.

Design/methodology/approach

The paper is conceptual and proposes a framework to explicate the phenomenon AI and its building blocks. It further provides a structured discussion of how AI can contribute to different types of market knowledge critical for B2B marketing: customer knowledge, user knowledge and external market knowledge.

Findings

The paper explains AI from an input–processes–output lens and explicates the six foundational building blocks of any AI system. It also discussed how the combination of the building blocks transforms data into information and knowledge.

Practical implications

Aimed at general marketing executives, rather than AI specialists, this paper explains the phenomenon artificial intelligence, how it works and its relevance for the knowledge-based marketing in B2B firms. The paper highlights illustrative use cases to show how AI can impact B2B marketing functions.

Originality/value

The study conceptualizes the technological phenomenon artificial intelligence from a knowledge management perspective and contributes to the literature on knowledge management in the era of big data. It addresses calls for more scholarly research on AI and B2B marketing.

Details

Journal of Business & Industrial Marketing, vol. 34 no. 7
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 1 May 1994

Norman M Fraser

The ESPRIT SUNDIAL project ran for five years, concluding in August 1993. The objective of the project was to design and build telephone‐access spoken language interfaces to…

Abstract

The ESPRIT SUNDIAL project ran for five years, concluding in August 1993. The objective of the project was to design and build telephone‐access spoken language interfaces to computer databases. After introducing the aims and objectives of the project, the problems of specifying an interactive system are outlined and the Wizard‐of‐Oz simulation method described. The architecture of the resulting system is introduced, and system transaction success results of up to 96.6% are reported. In the final section, some implications for machine translation — particularly interpretive telephony — are identified.

Details

Aslib Proceedings, vol. 46 no. 5
Type: Research Article
ISSN: 0001-253X

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