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The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

This study aims to introduce the design and the design process for an innovative sanitary fixture to be used in public facilities for the purpose of ablution. This purpose-made fixture is needed to support the hygienic, safe and comfortable performance of this essential function in public facilities in many parts of the world. The study also clarifies the need for this function and critically reviews current designs to address it.

The study started by critically reviewing the standard built-in models for ablution. It also identified and analyzed new approaches to designing standalone ablution fixtures. The study then specified the characteristics of a better ablution fixture and involved drafting a design based on these characteristics, making a wooden prototype to test the design and receiving users’ feedback. The design was adjusted and tested again for more feedback. Finally, the study resulted in the development of a final design. It used digital fabrication to create the design prototype with improved aesthetics, tested it again and received user feedback.

A survey of users showed that they found the innovative fixture more comfortable and safer than the commonly used built-in models. The main concern was the potential for water to splash on clothes from the high faucet.

In addition to showing an innovative design for a purpose-made sanitary fixture for ablution, the study makes the reader aware of the various challenges of providing a hygienic, safe and comfortable facility for users to perform this function. This is very useful for the many designers and facility managers who deal with the issue.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.