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排序方式： 共有683条查询结果，搜索用时 15 毫秒
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Kezban Dilek Onal Ye Zhang Ismail Sengor Altingovde Md Mustafizur Rahman Pinar Karagoz Alex Braylan Brandon Dang Heng-Lu Chang Henna Kim Quinten McNamara Aaron Angert Edward Banner Vivek Khetan Tyler McDonnell An Thanh Nguyen Dan Xu Byron C. Wallace Maarten de Rijke Matthew Lease 《Information Retrieval》2018,21(2-3):111-182
A recent “third wave” of neural network (NN) approaches now delivers state-of-the-art performance in many machine learning tasks, spanning speech recognition, computer vision, and natural language processing. Because these modern NNs often comprise multiple interconnected layers, work in this area is often referred to as deep learning. Recent years have witnessed an explosive growth of research into NN-based approaches to information retrieval (IR). A significant body of work has now been created. In this paper, we survey the current landscape of Neural IR research, paying special attention to the use of learned distributed representations of textual units. We highlight the successes of neural IR thus far, catalog obstacles to its wider adoption, and suggest potentially promising directions for future research. 相似文献
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Key points
- New forms of human/machine dialogue are emerging as robots understand vast amounts of content rather than simply indexing content as strings of characters.
- Recognizing strings of characters as entities (e.g. = names = authors) allows for meaningful associations between entities and reasoning over these relationships.
- Web‐scale adoption of the Semantic Web approach has been slow because it is too complex to implement and does not scale.
- User intent, discovered through conversational models of human–computer interaction, allows for a deeper understanding of exactly what researchers are looking for.
- Personal agents hold the promise of finding information that we will find useful before we have started to look for it.
- Publishers can use Academic Knowledge APIs to interpret academic user queries and find rich information from the Microsoft Academic Graph.
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Alex Pomson 《Education and Information Technologies》2008,13(2):147-163
This paper reports findings from a study of LookJed, the oldest and largest on-line forum for Computer Mediated Discussion
among individuals interested in Jewish education. The study adopted a “cyber-ethnographic” approach, with postings to the
forum seen as “acts of communication” that reveal what is important to their authors. An interest in exploring similarities
between forum conversations and those in teachers’ lounges led to an investigation of Herring’s claim that most listservs
do not include discussion at all, only the trading of information. This investigation found that active forum participants
generally use the forum for discrete purposes, most commonly to exchange information about “subject matter” or “teaching material”,
less commonly to exchange opinions and ideas, and rarely to do both. Integrating an analysis of patterns of contribution with
an examination of their discursive content reveals six preeminent “types” among the population of contributors, each of whom
participates in the forum in different ways and acts with different purposes. Although this typology is at best suggestive
and needs to be tested against other listserv cases, its easy identification suggests that in order to better understand the
cultures of virtual forums, it is important to pursue a more variegated characterization of listserv participants and their
motivations than has typically been the case in CMD research where users are most frequently identified as either lurkers
or fanatics, or as active or passive participants. 相似文献
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