scholarly journals Recommending High Utility Queries via Query-Reformulation Graph

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
JianGuo Wang ◽  
Joshua Zhexue Huang ◽  
Dingming Wu

Query recommendation is an essential part of modern search engine which aims at helping users find useful information. Existing query recommendation methods all focus on recommending similar queries to the users. However, the main problem of these similarity-based approaches is that even some very similar queries may return few or even no useful search results, while other less similar queries may return more useful search results, especially when the initial query does not reflect user’s search intent correctly. Therefore, we propose recommending high utility queries, that is, useful queries with more relevant documents, rather than similar ones. In this paper, we first construct a query-reformulation graph that consists of query nodes, satisfactory document nodes, and interruption node. Then, we apply an absorbing random walk on the query-reformulation graph and model the document utility with the transition probability from initial query to the satisfactory document. At last, we propagate the document utilities back to queries and rank candidate queries with their utilities for recommendation. Extensive experiments were conducted on real query logs, and the experimental results have shown that our method significantly outperformed the state-of-the-art methods in recommending high utility queries.

Author(s):  
Shanfeng Zhu ◽  
Xiaotie Deng ◽  
Qizhi Fang ◽  
Weimin Zhang

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.


2011 ◽  
Vol 52-54 ◽  
pp. 1218-1225
Author(s):  
Zheng Yu Zhu ◽  
Chun Lei Yu ◽  
Shu Jia Dong ◽  
Jie He

Current popular search engines are built to serve all users, independent of the needs of any individual user. A personalized query expansion method based on user's historical interested Web pages (UHIWPs) and user’s historical query terms (UHQTs) is proposed in this paper. When a user submits a query keyword to a search engine, the new algorithm can automatically locate the current user’s implicit search intention and compute the term-term associations dynamically according to the user’s UHIWPs and UHQTs. More personalized expansion terms then will be generated and submitted to the search engine together with the query keyword. As a result, different search results can be returned to different users even though they input the same query keywords. Experimental results show that this method is better than the current algorithm in average precision.


2013 ◽  
Vol 765-767 ◽  
pp. 1581-1584
Author(s):  
Lei Huang ◽  
Chan Le Wu

The resource getting core of knowledge Service System is the search engine, but the most studies only put attention to improve efficiency, so as to mass resources retrieval results still allows the user to face "cognitive overload" problem when the user to use searcher to get knowledge, how to provide personalized search results become a research focus. This paper provide a new personalized search ranking method, which use semantic tag and user profile to personalized the search results. The experimental results indicate that the method is effective.


2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Falah Hassan Ali Al-akashi

Shopping Search Engine (SSE) implies a unique challenge for validating distinct items available online in market place. For sellers, having a user listing appear number one in search results is crucial. Buyers tend to click on and buy from the listings which appear first. Search engine optimization devotes that goal to influence such challenges. In current shopping search platforms, lots of irrelevant itemsretrieved from their indices; e.g. retrieving accessories of exact items rather than retrieving the itemsitself, regardless the price of item were considered or not. In our proposal, we exploit the drawbacks of current shopping search engines. In another side, users tend to move from shoppers to another searching for appropriate items where the time is crucial for consumers. The main goal of this research is to combine and merge multiple search results retrieved from some popular shopping sellers in a listof relevant items. Experimental results showed that our approach is efficient and robust for retrieving acomplete list of desired items with respect to all users‟ query keywords.


Author(s):  
Yi Fan ◽  
Nan Li ◽  
Chengqian Li ◽  
Zongjie Ma ◽  
Longin Jan Latecki ◽  
...  

The Maximum Vertex Weight Clique (MVWC) problem is NP-hard and also important in real-world applications. In this paper we propose to use the restart and the random walk strategies to improve local search for MVWC. If a solution is revisited in some particular situation, the search will restart. In addition, when the local search has no other options except dropping vertices, it will use random walk. Experimental results show that our solver outperforms state-of-the-art solvers in DIMACS and finds a new best-known solution. Also it is the unique solver which is comparable with state-of-the-art methods on both BHOSLIB and large crafted graphs. Furthermore we evaluated our solver in clustering aggregation. Experimental results on a number of real data sets demonstrate that our solver outperforms the state-of-the-art for solving the derived MVWC problem and helps improve the final clustering results.


2013 ◽  
Vol 8 (1) ◽  
pp. 90 ◽  
Author(s):  
R. Laval Hunsucker

A Review of: Sahib, N. G., Tombros, A., & Stockman, T. (2012). A comparative analysis of the information-seeking behavior of visually impaired and sighted searchers. Journal of the American Society for Information Science and Technology, 63(2), 377–391. doi: 10.1002/asi.21696 Objective – To determine how the behaviour of visually impaired persons significantly differs from that of sighted persons in the carrying out of complex search tasks on the internet. Design – A comparative observational user study, plus semi-structured interviews. Setting – Not specified. Subjects – 15 sighted and 15 visually impaired persons, all of them experienced and frequent Internet search engine users, of both sexes and varying in age from early twenties to mid-fifties. Methods – The subjects carried out self-selected complex search tasks on their own equipment and in their own familiar environments. The investigators observed this activity to some extent directly, but for the most part via video camera, through use of a screen-sharing facility, or with screen-capture software. They distinguished four stages of search task activity: query formulation, search results exploration, query reformulation, and search results management. The visually impaired participants, of whom 13 were totally blind and two had only marginal vision, were all working with text-to-speech screen readers and depended exclusively for all their observed activity on those applications’ auditory output. For data analysis, the investigators devised a grounded-theory-based coding scheme. They employed a search log format for deriving further quantitative data which they later controlled for statistical significance (two-tailed unpaired t-test; p < 0.05). The interviews allowed them to document, in particular, how the visually impaired subjects themselves subsequently accounted for, interpreted, and vindicated various observed aspects of their searching behaviour. Main Results – The investigators found significant differences between the sighted participants’ search behaviour and that of the visually impaired searchers. The latter displayed a clearly less “orienteering” (O'Day & Jeffries, 1993) disposition and style, more often starting out with already relatively long and comprehensive combinations of relatively precise search terms; “their queries were more expressive” (p. 386). They submitted fewer follow-up queries, and were considerably less inclined to attempt query reformulation. They were aiming to achieve a satisfactory search outcome in a single step. Nevertheless, they rarely employed advanced operators, and made far less use (in only 4 instances) of their search engine’s query-support features than did the sighted searchers (37 instances). Fewer of them (13%) ventured beyond the first page of the results returned for their query by the search engine than was the case among the sighted searchers (43%). They viewed fewer (a mean of 4.27, as opposed to 13.40) retrieved pages, and they visited fewer external links (6 visits by 4 visually impaired searchers, compared with 34 visits by 11 sighted searchers). The visually impaired participants more frequently engaged in note taking than did the sighted participants. The visually impaired searchers were in some cases, the investigators discovered, unaware of search engine facilities or searching tactics which might have improved their search outcomes. Yet even when they were aware of these, they very often chose not to employ them because doing so via their screen readers would have cost them more time and effort than they were willing to expend. In general, they were more diffident and less resourceful than the sighted searchers, and had more trust in the innate capacity and reliability of their search engine to return in an efficient manner the best available results. Conclusion – Despite certain inherent limitations of the present study (the relatively small sample sizes and the non-randomness of the purposive sighted-searcher sample, the possible presence of extraneous variables, the impossibility of entirely ruling out familiarity bias), its findings strongly support the conclusion that working with today’s search engine user interfaces through the intermediation of currently available assistive technologies necessarily imposes severe limits on the degree to which visually impaired persons can efficiently search the web for information relevant to their needs. The findings furthermore suggest that there are various measures that it would be possible to take toward alleviating the situation, in the form of further improvements to retrieval systems, to search interfaces, and to text-to-speech screen readers. Such improvements would include: • more accessible system hints to support a better, and less cognitively intensive, query formulation; • web page layouts which are more suitable to screen-reader intermediation; • a results presentation which more readily facilitates browsing and exploratory behaviour, preferably including auditory previews and overviews; • presentation formats which allow for quicker and more accurate relevance judgments; • mechanisms for (a better) monitoring of search progress. In any event, further information behaviour studies ought now to be conducted, with the specific aim of more closely informing the development of user interfaces which will offer the kind of support that visually impaired Internet searchers are most in need of. Success in this undertaking will ultimately contribute to the further empowerment of visually disabled persons and thereby facilitate efforts to combat social exclusion.


2008 ◽  
pp. 1926-1937
Author(s):  
Shanfeng Chu ◽  
Xiaotie Deng ◽  
Qizhi Fang ◽  
Weimin Zhang

Web search engines are one of the most popular services to help users find useful information on the Web. Although many studies have been carried out to estimate the size and overlap of the general web search engines, it may not benefit the ordinary web searching users, since they care more about the overlap of the top N (N=10, 20 or 50) search results on concrete queries, but not the overlap of the total index database. In this study, we present experimental results on the comparison of the overlap of the top N (N=10, 20 or 50) search results from AlltheWeb, Google, AltaVista and WiseNut for the 58 most popular queries, as well as for the distance of the overlapped results. These 58 queries are chosen from WordTracker service, which records the most popular queries submitted to some famous metasearch engines, such as MetaCrawler and Dogpile. We divide these 58 queries into three categories for further investigation. Through in-depth study, we observe a number of interesting results: the overlap of the top N results retrieved by different search engines is very small; the search results of the queries in different categories behave in dramatically different ways; Google, on average, has the highest overlap among these four search engines; each search engine tends to adopt a different rank algorithm independently.


Author(s):  
Hamada M. Zahera ◽  
Gamal F. El-Hady ◽  
W. F. Abd El-Wahed

As web contents grow, the importance of search engines become more critical and at the same time user satisfaction decreases. Query recommendation is a new approach to improve search results in web. In this paper a method is proposed that, given a query submitted to a search engine, suggests a list of queries that are related to the user input query. The related queries are based on previously issued queries, and can be issued by the user to the search engine to tune or redirect the search process. The proposed method is based on clustering processes in which groups of semantically similar queries are detected. The clustering process uses the content of historical preferences of users registered in the query log of the search engine. This facility provides queries that are related to the ones submitted by users in order to direct them toward their required information. This method not only discovers the related queries but also ranks them according to a similarity measure. The method has been evaluated using real data sets from the search engine query log.


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