What and who with: A social approach to double-sided recommendation

Lombardi, Ilaria; Vernero, Fabiana

doi:10.1016/j.ijhcs.2017.01.001

Cited by 7 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With package recommendations, each suggestion consists in a set of items which are expected to be consumed "together" [3]. Examples of packages are playlists of songs or movies, travel plans or sets of points of interest which can be visited as part of a single trip, bundles of products which can be bought together, as well as teams of players or co-workers or a single item, such as a restaurant, accompanied by a group of people with whom that item can be enjoyed [30]. Sequence recommendations (see, e.g., [42]) extend the package concept by including temporal constraints on item consumption.…”

Section: Package Recommendationsmentioning

confidence: 99%

See 1 more Smart Citation

Logical foundations of knowledge-based recommender systems: A unifying spectrum of alternatives

Cena

Console

Vernero

2021

Information Sciences

Self Cite

View full text Add to dashboard Cite

The aim of this paper is to provide logical foundations for knowledge-based recommender systems, for which, unlike other problem solving tasks, a comprehensive formalization is not yet available. This goal is justified by the need to compare recommenders based on the way they use knowledge to generate recommendations and, consequently, on the underlying semantics of the recommendation process itself. Moreover, since the here adopted logical formalization has been borrowed from other tasks such as diagnosis, many interesting results and opportunities can be transposed from such tasks to recommendation. While we do not aim at proposing a new recommendation generation technique, we believe that our formalization will be the basis for unifying different approaches to knowledge-based recommendation, revealing their semantics and offering a conceptual framework to compare them. In fact, the framework covers different variations of knowledge-based recommendation, such as context-aware, constraints-based, package and group recommendation, as well as recommendation based on negative preferences.

show abstract

Section: Package Recommendationsmentioning

confidence: 99%

“…In those cases where a solution that satisfies all the users in the group cannot be found, it may be interesting to suggest also which is the "best group" for each one of the identified solutions, thus generating "mixed" packages of groups and items, similarly to [30].…”

Section: Group Recommendationmentioning

confidence: 99%

Logical foundations of knowledge-based recommender systems: A unifying spectrum of alternatives

Cena

Console

Vernero

2021

Information Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…The change brought to online consumer behaviors through contentrich social networking sites has led to changes in some of the criteria related to hotel preferences in TripAdvisor. Even the simplest form of criteria, being positive or negative opinions and comments about hotels, can have an impact on consumer behavior (Anderson, 2012;Yang & Chao, 2015;Chen & Law, 2016;Chen & Ng, 2017;Lombardi & Vernero, 2017;Tsao et al, 2018). An analysis of studies investigating this effect reveals that positive or negative opinions and comments influence consumer behaviors.…”

Section: Literature Reviewmentioning

confidence: 99%

The Effects on Consumer Behavior of Hotel Related Comments on the TripAdvisor Website: An Istanbul Case

Yilmaz

2020

Advances in Hospitality and Tourism Research (AHTR)

View full text Add to dashboard Cite

In parallel with the major developments witnessed in information technologies, social media, supported by its broad area of usage, is gaining significance in every field, with the tourism sector being no exception in this regard. The transfer of changing marketing strategies via digital channels into social media has transformed the way customers interact with the tourism sector, having now the ability to access the comments of other consumers via social media, and adjusting their preferences accordingly. In this study, the impact of the content analysis on the star rating given to hotels is examined with a "Panel Data Analysis" of all the hotels in Istanbul that have received a maximum of 25 reviews on the TripAdvisor website, with a total of 12,000 comments assessed. It was found that the location of the hotel, the access to transport facilities, the food and beverage concept, the quality of staff/service, and the cleanliness of the facilities all affected the star ratings given to hotels; while the architectural structure and the recommendations of other guests had a lesser effect. It was further noted that entertainmentanimation programs had little effect on guest preferences.

show abstract

“…Need to process multilingual information Collaborative filtering (Lombardi & Vernero, 2017) Users with similar behaviors have the same preferences, so it can recommend items of interest to users with similar behaviors…”

Section: Basic Principal Merits Shortagesmentioning

confidence: 99%

“…Service recommendation methods can effectively solve the issues of information overload and recommend items of interest to users. Currently, service recommendation methods mainly include the content-based recommendation method (Narducci et al, 2016), the collaborative filtering recommendation method (Lombardi & Vernero, 2017), the knowledge-based recommendation method (Qiao et al, 2014), the trust model-based recommendation method (Lu et al, 2018), the tag-based recommendation method (Bogers, 2018) and the combined recommendation method (Zhao et al, 2017;Wei et al, 2017). The comparison of the basic ideas, merits and shortages of each method are shown in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Survey of Intelligent Recommendation of Academic Information in University Libraries Based on Situational Perception Method

Liu¹

2020

JEL

View full text Add to dashboard Cite

Based on the context-aware environment, in this paper, the adaptive interest models are reviewed. And the academic information intelligent recommendation systems of university libraries are presented based on the situational awareness-related theory method, where the current situation and trend of situational awareness-related theory and service of intelligent recommendation systems are investigated. Meanwhile, the potential research directions, basic ideas and methods are also presented. The adaptive model and architecture of the academic information recommendation system are built based on situational awareness, and the collaborative filtering information recommendation algorithm is studied based on spatial-temporal similarity relationship to obtain the interest of scientific and technological scholars. Combining with the adaptive interest model, an academic information demand model is established. On this basis, the prototype system of academic information recommendation is further studied to realize personalized recommendation of academic information based on the situational perception. This paper will provide effective solutions to the digital resources service of university libraries and the academic information recommendation needs of scientific and technological scholars.In this paper, the situational awareness-related theory (SART) methods are investigated in the information service of university libraries, which is derived as the university libraries academic information intelligent recommendation system (IRS). In general, the IRS can automatically obtain and make use of the location, environment, scientists' and technicians' behavior and situation information. Then, according to the information, intelligent adaptive interest measuring model of scientists and technicians can be constructed, and the relevant similarity clustering algorithm and the collaborative filtering technology are presented to improve the recommended academic information based on the features of university libraries. In this way, the quality of academic information service of university libraries can be then improved. Literature ReviewThis paper presents the academic information IRS of university libraries based on the SART method, in which the current situation and trend of SART and service of IRS are investigated. Schilit firstly proposed the concept

show abstract

What and who with: A social approach to double-sided recommendation

Cited by 7 publications

References 38 publications

Logical foundations of knowledge-based recommender systems: A unifying spectrum of alternatives

Logical foundations of knowledge-based recommender systems: A unifying spectrum of alternatives

The Effects on Consumer Behavior of Hotel Related Comments on the TripAdvisor Website: An Istanbul Case

Survey of Intelligent Recommendation of Academic Information in University Libraries Based on Situational Perception Method

Contact Info

Product

Resources

About