Search results for "Pity"
showing 8 items of 38 documents
Serendipity in recommender systems
2018
The number of goods and services (such as accommodation or music streaming) offered by e-commerce websites does not allow users to examine all the available options in a reasonable amount of time. Recommender systems are auxiliary systems designed to help users find interesting goods or services (items) on a website when the number of available items is overwhelming. Traditionally, recommender systems have been optimized for accuracy, which indicates how often a user consumed the items recommended by system. To increase accuracy, recommender systems often suggest items that are popular and suitably similar to items these users have consumed in the past. As a result, users often lose interest…
Challenges of Serendipity in Recommender Systems
2016
Most recommender systems suggest items similar to a user profile, which results in boring recommendations limited by user preferences indicated in the system. To overcome this problem, recommender systems should suggest serendipitous items, which is a challenging task, as it is unclear what makes items serendipitous to a user and how to measure serendipity. The concept is difficult to investigate, as serendipity includes an emotional dimension and serendipitous encounters are very rare. In this paper, we discuss mentioned challenges, review definitions of serendipity and serendipity-oriented evaluation metrics. The goal of the paper is to guide and inspire future efforts on serendipity in r…
The Gospel of St John in Literature
1997
‘Idou ho anthropos’ (Latin Ecce homo, ‘Behold the man’) are the words used by Pilate in presenting Jesus to the Jews, bound, scourged, crowned with thorns, and wearing a purple robe (John 19:15). Most interpreters of Pilate’s laconic statement have taken Ecce homo to mean, ‘Here is the poor fellow!’, the speaker’s rhetoric having the purpose of eliciting pity from the spectators, or contemptuously ridiculing the Jews for taking such a lowly and risible figure’s claim to kingship over them so seriously, or provoking them into demanding Christ’s release. Among those exegetes interested in drawing out the theological implications of Pilate’s pronouncement, some suggest that John here emphasize…
Pityriasis rosea Gibert triggered by SARS-CoV-2 infection: A case report.
2021
RATIONALE: Pityriasis rosea Gibert is an erythematous-papulosquamous dermatosis that frequently occurs in young adults. The etiopathogenesis of PR is still unknown, but is frequently associated with episodes of upper respiratory tract infections. It is likely that a new viral trigger of pityriasis rosea is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). PATIENT CONCERNS: We present the case of a female patient in whom the diagnosis of pityriasis rosea led to the investigation and diagnosis of the SARS-CoV-2 infection. The patient presented to the Department of Dermatology for a 3âweek duration of an extremely pruritic erythematous-squamous lesion, initially on the trunk …
Investigating serendipity in recommender systems based on real user feedback
2018
Over the past several years, research in recommender systems has emphasized the importance of serendipity, but there is still no consensus on the definition of this concept and whether serendipitous items should be recommended is still not a well-addressed question. According to the most common definition, serendipity consists of three components: relevance, novelty and unexpectedness, where each component has multiple variations. In this paper, we looked at eight different definitions of serendipity and asked users how they perceived them in the context of movie recommendations. We surveyed 475 users of the movie recommender system, MovieLens regarding 2146 movies in total and compared tho…
A Serendipity-Oriented Greedy Algorithm for Recommendations
2017
Most recommender systems suggest items to a user that are popular among all users and similar to items the user usually consumes. As a result, a user receives recommendations that she/he is already familiar with or would find anyway, leading to low satisfaction. To overcome this problem, a recommender system should suggest novel, relevant and unexpected, i.e. serendipitous items. In this paper, we propose a serendipity-oriented algorithm, which improves serendipity through feature diversification and helps overcome the overspecialization problem. To evaluate our algorithm and compare it with others, we employ a serendipity metric that captures each component of serendipity, unlike the most …
Recommending Serendipitous Items using Transfer Learning
2018
Most recommender algorithms are designed to suggest relevant items, but suggesting these items does not always result in user satisfaction. Therefore, the efforts in recommender systems recently shifted towards serendipity, but generating serendipitous recommendations is difficult due to the lack of training data. To the best of our knowledge, there are many large datasets containing relevance scores (relevance oriented) and only one publicly available dataset containing a relatively small number of serendipity scores (serendipity oriented). This limits the learning capabilities of serendipity oriented algorithms. Therefore, in the absence of any known deep learning algorithms for recommend…