Clarifying Ambiguous Keywords with Personal Word Embeddings for Personalized Search

Personalized search tailors document ranking lists for each individual user based on her interests and query intent to better satisfy the user’s information need. Many personalized search models have been proposed. They first build a user interest profile from the user’s search history, and then re-rank the documents based on the personalized matching scores between the created profile and candidate documents. In this article, we attempt to solve the personalized search problem from an alternative perspective of clarifying the user’s intention of the current query. We know that there are many ambiguous words in natural language such as “Apple.” People with different knowledge backgrounds and interests have personalized understandings of these words. Therefore, we propose a personalized search model with personal word embeddings for each individual user that mainly contain the word meanings that the user already knows and can reflect the user interests. To learn great personal word embeddings, we design a pre-training model that captures both the textual information of the query log and the information about user interests contained in the click-through data represented as a graph structure. With personal word embeddings, we obtain the personalized word and context-aware representations of the query and documents. Furthermore, we also employ the current session as the short-term search context to dynamically disambiguate the current query. Finally, we use a matching model to calculate the matching score between the personalized query and document representations for ranking. Experimental results on two large-scale query logs show that our designed model significantly outperforms state-of-the-art personalization models.

STARec: Adaptive Learning with Spatiotemporal and Activity Influence for POI Recommendation

POI recommendation has become an essential means to help people discover attractive places. Intuitively, activities have an important impact on users’ decision-making, because users select POIs to attend corresponding activities. However, many existing studies ignore the social motivation of user behaviors and regard all check-ins as influenced only by individual user interests. As a result, they cannot model user preferences accurately, which degrades recommendation effectiveness. In this article, from the perspective of activities, this study proposes a probabilistic generative model called STARec. Specifically, based on the social effect of activities, STARec defines users’ social preferences as distinct from their individual interests and combines these with individual user activity interests to effectively depict user preferences. Moreover, the inconsistency between users’ social preferences and their decisions is modeled. An activity frequency feature is introduced to acquire accurate user social preferences because of close correlation between these and the key impact factor of corresponding check-ins. An alias sampling-based training method was used to accelerate training. Extensive experiments were conducted on two real-world datasets. Experimental results demonstrated that the proposed STARec model achieves superior performance in terms of high recommendation accuracy, robustness to data sparsity, effectiveness in handling cold-start problems, efficiency, and interpretability.

Seismic Performance Assessment of Water Distribution Systems Based on Multi-Indexed Nodal Importance

Seismic performance assessment of water distribution systems (WDSs) based on hydraulic simulation is essential for resilience evaluation of WDSs under earthquake disasters. The assessment is mainly to determine how the water supply will be affected due to pipe breaks caused by the earthquake, with the water supply loss estimated based on the loss of supply to nodes. Existing research works usually use the average or overall performance metric of all user nodes as the system performance indicator without considering user nodes’ individual performance and criticality. This paper proposes a framework to evaluate the importance of user nodes considering post-earthquake rescue service and the seismic performance of individual user nodes in the WDS, which supports the pipeline renovation plan to improve the performance of critical user nodes. The importance of user nodes is evaluated by a multi-index model, including the indices for daily service, post-earthquake rescue service, and network topology influence of user nodes. These indices evaluate the importance of user nodes in terms of their roles for daily water service, emergent rescue service, and water transmission to other nodes, respectively. Fragility model of pipelines evaluates the earthquake-induced damages of the WDS, and the seismic performance assessment of the WDS system is performed by the hydraulic model of the WDS with pipeline damages. The proposed framework is implemented in an actual WDS; the results show that the importance classification to user nodes by multi-index approach can identify the critical user nodes for post-earthquake rescue service, which traditional methods may ignore. The importance classification and seismic performance of individual user nodes make it feasible to check the seismic performance of critical user nodes and formulate a targeted pipeline renovation plan to focus limited resources on critical user nodes.

Digital semaphore: Political discourse and identity negotiation through 4chan’s /pol/

This article explores the ways in which Blommaert’s (2018) notion of “light” identity markers in digital spaces shows—through specific features within /pol/—the “politically incorrect” board of the popular anonymous imageboard website 4chan. Here, flags attached to individual user posts work to frame interaction, which can both signal sincerity to a post with a national flag, or demonstrate a predilection for deception and trolling with what is known as a “memeflag.” Users implement these choices to alter performative aspects of interaction on /pol/ and the “audience” of other users offer their own evaluations, dismissals, and jokes in the face of these displays. This article posits that “light” identity features, or those located within specific communities, as opposed to more widespread or institutionalized aspects of identities create categories of awareness in 4chan that, in turn, shapes ideas of competence for those who have “lurked” long enough to glean it.

Basket of options: Unpacking the concept

How to stimulate technological change to enhance agricultural productivity and reduce poverty remains an area of vigorous debate. In the face of heterogeneity among farm households and rural areas, one proposition is to offer potential users a ‘basket of options’ – a range of agricultural technologies from which potential users may select the ones that are best suited to their specific circumstances. While the idea of a basket of options is now generally accepted, it has attracted little critical attention. In this paper, we reflect on outstanding questions: the appropriate dimensions of a basket, its contents and how they are identified, and how a basket might be presented. We conceive a basket of options in terms of its depth (number of options related to a problem or opportunity) and breadth (the number of different problems or opportunities addressed). The dimensions of a basket should reflect the framing of the problem or opportunity at hand and the objective in offering the basket. We recognise that increasing the number of options leads to a trade-off by decreasing the fraction of those options that are relevant to an individual user. Farmers might try out, adapt or use one or more of the options in a basket, possibly leading to a process of technological change. We emphasise that the selection (or not) of specific options from the basket, and potential adaptation of the options, provide important opportunities for learning. Baskets of options can therefore be understood as important boundary concepts that invite critical engagement, comparison and discussion. Significant knowledge gaps remain, however, about the best ways to present the basket and to guide potential users to select the options that are most relevant to them.

Not Tracking: The Antipolitics of Contact-Tracing Applications

In response to the COVID-19 pandemic, governments around the world turned to contact-tracing applications in an attempt to balance the reopening of the economy with keeping the virus at bay. But as this article demonstrates, contact-tracing applications not only fail to protect the most vulnerable among us; they also shift responsibility for failing to prepare public-health systems for a pandemic away from governments and onto the individual user struggling to contain its worst effects. In the process, contact-tracing applications change the definition of failure. They also reinforce existing inequalities. Technology in this case not only has politics; it prevents politics. By focusing on contact-tracing applications as an example, the article points to some of the deeper perils of accepting app-based solutions to structural problems.

Using User Journey to map emotional oscillations during CoVID-19 social distancing

The CoVid-19 pandemic has demanded society to social distance, which significantly affected not only people's routine but also and their mental health. The way each person is facing this period of confinement is shaped according to their principles, culture, health, and financial stability, thus leading individuals to react emotionally in different ways. Through Design, it is possible to map these experiences and represent them through User Journeys, allowing clear representations of how the experience took place when facing the fear of contagion, the sudden change of routine, and isolation. This study focuses on discussing the effectiveness of unifying different experiences in a single representation, mainly to outline emotional aspects. Trying to balance all emotional variations in a single User Journey prevents the researcher from seeing important details of the users' experience. In this study, the need to use individual User Journeys was evidenced when it is intended to analyse the emotional aspects of users when dealing with products or services, as individuality can shed light on aspects not observable in a consolidated analysis.

User Interfaces

This report shows, that the impact of a good User Interfaces (UI) is not only affecting the usability and comfort for the user, but is also a major key to save energy. At least as important for effectiveness to the quality of individual interfaces is consistency in the meaning of individual user interface elements (visual, conceptual, auditory, etc.)

Defeating MITM Attacks on Cryptocurrency Exchange Accounts with Individual User Keys

Presented herein is a User-SpecificKey Scheme based on Elliptic Curve Cryptography that defeats man-inthe-middle attacks on cryptocurrency exchange accounts. In this scheme, a separate public and private key pair is assigned to every account and the public key is shifted either forward or backward on the elliptic curve by a difference of the account user’s password. When a user logs into his account, the server sends the shifted public key of his account. The user computes the actual public key of his account by reverse shifting the shifted public key exactly by a difference of his password. Alternatively, shifting can be applied to the user’s generator instead of the public key. Described in detail is as to how aman-in-the-middle attack takes place and how the proposed scheme defeats the attack. Provided detailed security analysis in both the cases of publickey shifting and generator shifting. Further, compared the effectiveness of another three authentication schemes in defending passwords against MITM attacks.