Search results for "Trie"
showing 10 items of 4468 documents
Fluorinated heterocyclic compounds: an assay on the photochemistry of some fluorinated 1-oxa-2-azoles: an expedient route to fluorinated heterocycles
2004
Abstract Photoinduced heterocyclic rearrangements of ON bond-containing azoles have been claimed in the synthesis of target fluorinated heterocyclic compounds. In this context, the photochemical behavior of some fluorinated 1,2,4-oxadiazoles has been investigated. Irradiations of 3-amino-5-perfluoroalkyl-1,2,4-oxadiazoles at λ =313 nm in methanol gave open-chain products arising from a reaction of the nucleophilic solvent with either the first formed ring-photolytic species or with a nitrilimine moiety generated from it. Differently, irradiations in methanol with the presence of triethylamine (TEA) followed competing phototransposition pathways leading to the ring-isomers 2-amino-5-perfluo…
Generalizability and Simplicity as Criteria in Feature Selection: Application to Mood Classification in Music
2011
Classification of musical audio signals according to expressed mood or emotion has evident applications to content-based music retrieval in large databases. Wrapper selection is a dimension reduction method that has been proposed for improving classification performance. However, the technique is prone to lead to overfitting of the training data, which decreases the generalizability of the obtained results. We claim that previous attempts to apply wrapper selection in the field of music information retrieval (MIR) have led to disputable conclusions about the used methods due to inadequate analysis frameworks, indicative of overfitting, and biased results. This paper presents a framework bas…
A Cooperative Coevolution Framework for Parallel Learning to Rank
2015
We propose CCRank, the first parallel framework for learning to rank based on evolutionary algorithms (EA), aiming to significantly improve learning efficiency while maintaining accuracy. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed sub-problems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. We implement CCRank with three EA-based learning to rank algorithms for demonstration. E…
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 Hybrid Multigroup Coclustering Recommendation Framework Based on Information Fusion
2015
Collaborative Filtering (CF) is one of the most successful algorithms in recommender systems. However, it suffers from data sparsity and scalability problems. Although many clustering techniques have been incorporated to alleviate these two problems, most of them fail to achieve further significant improvement in recommendation accuracy. First of all, most of them assume each user or item belongs to a single cluster. Since usually users can hold multiple interests and items may belong to multiple categories, it is more reasonable to assume that users and items can join multiple clusters (groups), where each cluster is a subset of like-minded users and items they prefer. Furthermore, most of…
Cross-Domain Recommendations with Overlapping Items
2016
In recent years, there has been an increasing interest in cross-domain recommender systems. However, most existing works focus on the situation when only users or users and items overlap in different domains. In this paper, we investigate whether the source domain can boost the recommendation performance in the target domain when only items overlap. Due to the lack of publicly available datasets, we collect a dataset from two domains related to music, involving both the users’ rating scores and the description of the items. We then conduct experiments using collaborative filtering and content-based filtering approaches for validation purpose. According to our experimental results, the sourc…
User session level diverse reranking of search results
2018
Most Web search diversity approaches can be categorized as Document Level Diversification (DocLD), Topic Level Diversification (TopicLD) or Term Level Diversification (TermLD). DocLD selects the relevant documents with minimal content overlap to each other. It does not take the coverage of query subtopics into account. TopicLD solves this by modeling query subtopics explicitly. However, the automatic mining of query subtopics is difficult. TermLD tries to cover as many query topic terms as possible, which reduces the task of finding a query's subtopics into finding a set of representative topic terms. In this paper, we propose a novel User Session Level Diversification (UserLD) approach bas…
Guidelines for improving the contextual relevance of field surveys: the case of information security policy violations
2014
The information systems (IS) field continues to debate the relative importance of rigor and relevance in its research. While the pursuit of rigor in research is important, we argue that further effort is needed to improve practical relevance, not only in terms of topics, but also by ensuring contextual relevance. While content validity is often performed rigorously, validated survey instruments may still lack contextual relevance and be out of touch with practice. We argue that IS behavioral research can improve its practical relevance without loss of rigor by carefully addressing a number of contextual issues in instrumentation design. In this opinion article, we outline five guidelines – …
Flexible entity search on surfaces
2016
Surface computing allows flexible search interaction where users can manipulate the representation of entities recommended for them to create new queries or augment existing queries by taking advantage of increased screen estate and almost physical tactile interaction. We demonstrate a search system based on 1) Direct Manipulation of Entity Representation on Surfaces and 2) Entity Recommendation and Document Retrieval. Entities are modeled as a knowledge-graph and the relevances of entities are computed using the graph structure. Users can manipulate the representation of entities via spatial grouping and assigning preferences on entities. Our contribution can help to design effective infor…
A two-step, user-centered approach to personalized tourist recommendations
2017
Geo-localized, mobile applications can simplify a tourist visit, making the relevant Point of Interests more easily and promptly discernible to users. At the same time, such solutions must avoid creating unfitting or rigid user profiles that impoverish the users' options instead of refining them. Currently, user profiles in recommender systems rely on dimensions whose relevance to the user is more often presumed than empirically defined. To avoid this drawback, we build our recommendation system in a two-step process, where profile parameters are evaluated preliminarily and separately from the recommendations themselves. We describe this two-step evaluation process including an initial surv…