4 research outputs found
Location Aware Keyword Query Suggestion Based on Document Proximity
Abstract—Keyword suggestion in web search helps users to access relevant information without having to know how to precisely express their queries. Existing keyword suggestion techniques do not consider the locations of the users and the query results; i.e., the spatial proximity of a user to the retrieved results is not taken as a factor in the recommendation. However, the relevance of search results in many applications (e.g., location-based services) is known to be correlated with their spatial proximity to the query issuer. In this paper, we design a location-aware keyword query suggestion framework. We propose a weighted keyword-document graph, which captures both the semantic relevance between keyword queries and the spatial distance between the resulting documents and the user location. The graph is browsed in a random-walk-with-restart fashion, to select the keyword queries with the highest scores as suggestions. To make our framework scalable, we propose a partition-based approach that outperforms the baseline algorithm by up to an order of magnitude. The appropriateness of our framework and the performance of the algorithms are evaluated using real data. F
查询推荐研究综述
查询推荐是一种提高用户搜索效率的重要技术,其核心任务是帮助用户构造有效查询并以此准确描述用户信息需求。作为当今搜索引擎的核心技术之一,查询推荐吸引了学术界和工业界的广泛关注,一直以来都是信息检索领域中重要的研究主题。本文以国内外会议、期刊发表的有关查询推荐研究的文献为对象,利用归纳总结方法,首先详细梳理了查询推荐中主流方法——基于简单共现信息的方法、基于图模型的方法以及融合多种信息的方法,然后总结评述了评测方法与指标,最后分析了未来可能的研究方向。</p
A location-query-browse graph for contextual recommendation
Traditionally, recommender systems modelled the physical and cyber contextual influence on people's moving, querying, and browsing behaviours in isolation. Yet, searching, querying and moving behaviours are intricately linked, especially indoors. Here, we introduce a tripartite location-query-browse graph (LQB) for nuanced contextual recommendations. The LQB graph consists of three kinds of nodes: locations, queries and Web domains. Directed connections only between heterogeneous nodes represent the contextual influences, while connections of homogeneous nodes are inferred from the contextual influences of the other nodes. This tripartite LQB graph is more reliable than any monopartite or bipartite graph in contextual location, query and Web content recommendations. We validate this LQB graph in an indoor retail scenario with extensive dataset of three logs collected from over 120,000 anonymized, opt-in users over a 1-year period in a large inner-city mall in Sydney, Australia. We characterize the contextual influences that correspond to the arcs in the LQB graph, and evaluate the usefulness of the LQB graph for location, query, and Web content recommendations. The experimental results show that the LQB graph successfully captures the contextual influence and significantly outperforms the state of the art in these applications
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Design and Implementation of System Components for Radio Frequency Based Asset Tracking Devices to Enhance Location Based Services. Study of angle of arrival techniques, effects of mutual coupling, design of an angle of arrival algorithm, design of a novel miniature reconfigurable antenna optimised for wireless communication systems
The angle of arrival estimation of multiple sources plays a vital role in the field of array signal
processing as MIMO systems can be employed at both the transmitter and the receiver end
and the system capacity, reliability and throughput can be significantly increased by using array
signal processing. Almost all applications require accurate direction of arrival (DOA) estimation
to localize the sources of the signals. Another important parameter of localization systems is
the array geometry and sensor design which can be application specific and is used to
estimate the DOA.
In this work, various array geometries and arrival estimation algorithms are studied and then a
new scheme for multiple source estimation is proposed and evaluated based on the
performance of subspace and non-subspace decomposition methods. The proposed scheme
has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation
and Bartlett estimation techniques. The new scheme has a better performance advantage at
low and high signal to noise ratio values (SNRs).
The research work also studies different array geometries for both single and multiple incident
sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna
array elements. This research also considers the shape of the ground plane and its effects on
the angle of arrival estimation and in addition it shows how the mutual couplings between the
elements effect the overall estimation and how this error can be minimised by using a decoupling
matrix.
At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver
base station is designed and tested. The antenna radiation patterns in the azimuth angle are
almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral
with striplines feeding network and biased components to improve the impedance
bandwidth. The antenna provides the benefit of small size, and re-configurability and is very
well suited for the asset tracking applications