Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things. This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems, identifies areas of future implementation and develops certain areas selected for past, present or future importance.

http://romisatriawahono.net/lecture/rm/survey/information%20retrieval/Bobadilla%20-%20Recommender%20Systems%20-%202013.pdf

Recommender systems survey

The relative ineffectiveness of information retrieval systems is largely caused by the inaccuracy with which a query formed by a few keywords models the actual user information need. One well known method to overcome this limitation is automatic query expansion (AQE), whereby the user’s original query is augmented by new features with a similar meaning. AQE has a long history in the information retrieval community but it is only in the last years that it has reached a level of scientific and experimental maturity, especially in laboratory settings such as TREC. This survey presents a unified view of a large number of recent approaches to AQE that leverage various data sources and employ very different principles and techniques. The following questions are addressed. Why is query expansion so important to improve search effectiveness? What are the main steps involved in the design and implementation of an AQE component? What approaches to AQE are available and how do they compare? Which issues must still be resolved before AQE becomes a standard component of large operational information retrieval systems (e.g., search engines)?

/pdf/a-survey-of-automatic-query-expansion-in-information-30cfvdlacg.pdf

A Survey of Automatic Query Expansion in Information Retrieval

The article reviews the book “Information Rules: A Strategic Guide to the Network Economy,” by Carl Shapiro and Hal R. Varian.

Information Rules: A Strategic Guide to the Network Economy

我的台灣, 看見心靈的故鄉 =2009林磐聳藝術與設計展

We present a syntax-based statistical translation model. Our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each node. These operations capture linguistic differences such as word order and case marking. Model parameters are estimated in polynomial time using an EM algorithm. The model produces word alignments that are better than those produced by IBM Model 5.

https://faculty.washington.edu/fxia/courses/LING580MT/yamada_2001.pdf

A Syntax-based Statistical Translation Model

Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented perspective toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues—such as evaluation, targeting, and privacy and trust—which we also briefly address.

/pdf/recommender-systems-research-a-connection-centric-survey-4ysnzqnm49.pdf

Recommender Systems Research: A Connection-Centric Survey

We describe four usability-enhancing interfaces to CITIDEL aimed at improving the user experience and supporting personalized information access by targeted communities. These comprise: a multimodal interaction facility with capability for out-of-turn input, interactive visualizations for exploratory analysis, a translation center exposing multilingual interfaces, as well as traditional usability enhancements. Pilot studies demonstrate the resulting improvements in quality, as measured across a number of metrics.

/pdf/enhancing-usability-in-citidel-multimodal-multilingual-and-4k7nhbyexc.pdf

Enhancing usability in CITIDEL: multimodal, multilingual, and interactive visualization interfaces

Personalization refers to the automatic adjustment of information content, structure, and presentation tailored to an individual user. Commercial Web sites increasingly employ personalization to help retain customers and reduce information overload. A Web site is personalized if a user can interact with the site in an expressive way to achieve his information-seeking goals. Thus, personalizing the user's interaction is the best way to achieve personalization. The paper discusses mixed initiative interaction and the use of XSLT for personalization.

Personalizing Web sites with mixed-initiative interaction

We present the first user study of out-of-turn interaction inmenu-based, interactive voice-response systems. Out-of-turn interaction is atechnique which empowers the user (unable to respond to the current prompt) totake the conversational initiative by supplying information that is currentlyunsolicited, but expected later in the dialog. The technique permits the userto circumvent any flows of navigation hardwired into the design and navigatethe menus in a manner which reflects their model of the task. We conducted alaboratory experiment to measure the effect of the use of out-of-turninteraction on user performance and preference in a menu-based, voice interfaceto voicemail. Specifically, we compared two interfaces with the exact samehierarchical menu design: one with the capability of accepting out-of-turnutterances and one without this feature. The results indicate that out-of-turninteraction significantly reduces task completion time, improves usability, andis preferred to the baseline. This research studies an unexplored dimension ofthe design space for automated telephone services, namely the nature ofuser-addressable input (utterance) supplied (in-turn vs. out-of-turn), incontrast to more traditional dimensions such as input modality (touch-tone vs.text vs. voice) and style of interaction (menu-based vs. natural language).

/pdf/a-study-of-out-of-turn-interaction-in-menu-based-ivr-tw3d6i8w2w.pdf

A study of out-of-turn interaction in menu-based, IVR, voicemail systems

We present three fundamental, interrelated approaches to support multiple access paths to each terminal object in information hierarchies: faceted classification, faceted search, and web directories with embedded symbolic links. This survey aims to demonstrate how each approach supports users who seek information from multiple perspectives. We achieve this by exploring each approach, the relationships between these approaches, including tradeoffs, and how they can be used in concert, while focusing on a core set of hypermedia elements common to all. This approach provides a foundation from which to study, understand, and synthesize applications which employ these techniques. This survey does not aim to be comprehensive, but rather focuses on thematic issues.

/pdf/supporting-multiple-paths-to-objects-in-information-1ae0ps1yr4.pdf

Saverio Perugini

Papers

Recommender Systems Research: A Connection-Centric Survey

Enhancing usability in CITIDEL: multimodal, multilingual, and interactive visualization interfaces

Personalizing Web sites with mixed-initiative interaction

A study of out-of-turn interaction in menu-based, IVR, voicemail systems

Supporting multiple paths to objects in information hierarchies: Faceted classification, faceted search, and symbolic links