Browsing Experience Research Articles

Emotion detection on webpages using biosensors integrated to a window-based dynamic control system

PurposeDetecting emotion on user experience of web applications and browsing is important in many ways. Web designers and developers find such approach quite useful in enhancing navigational features of webpages, and biomedical personnel regularly use computer simulations to monitor and control the behaviour of patients. On the other hand, law enforcement agents rely on human physiological functions to determine the likelihood of falsehood in interrogations. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users' emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors.Design/methodology/approachThe authors propose a novel method-a window dynamic control system that addresses the foregoing issues. Primary data were obtained from laboratory experiments during which forty-four volunteers had their synchronised physiological readings, skin conductance response (SCR), skin temperature (ST), eye movement behaviour and users’ activity attributes taken using biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronised physiological readings and uses them for two purposes. For both detection of optimal emotional responses and users' stress levels. The method's novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage.FindingsResults show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods.Research limitations/implicationsThe paper is limited to using a window control system to detect emotions on webpages, while integrated to biosensors and eye-tracker.Originality/valueThe originality of the proposed model is its resistance to overfitting and its ability to automatically assess human emotion (stress levels) while dealing with specific web contents. The latter is particularly important in that it can be used to predict which contents of webpages cause stress-induced emotions to users when involved in online activities.

Integration of biosensor to a window-based control system for user emotion detection to static and dynamic visual contents of webpages

Purpose Basic capturing of emotion on user experience of web applications and browsing is important in many ways. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users’ emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. This paper aims to propose a novel method – a window dynamic control system – that addresses the foregoing issues. Design/methodology/approach Primary data were obtained from laboratory experiments during which 44 volunteers had their synchronized physiological readings – skin conductance response, skin temperature, eye movement behaviour and users activity attributes taken by biosensors. The window-based dynamic control system (PHYCOB I) is integrated to the biosensor which collects secondary data attributes from these synchronized physiological readings and uses them for two purposes: for detection of both optimal emotional responses and users’ stress levels. The method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a webpage. Findings The results from the analyses show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability, when subjected to model comparison – that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the window-based control system environment than with the conventional methods. Research limitations/implications Graphical simulation and an example scenario are only provided for the control’s system design. Originality/value The novelty of the proposed model is its strained resistance to overfitting and its ability to automatically assess user emotion while dealing with specific web contents. The procedure can be used to predict which contents of webpages cause stress-induced emotions to users.

Casual Leisure in Rich-Prospect

As digital cultural collections become increasingly sophisticated in their scope and functionality, there is a need to build an in-depth understanding concerning the information behaviors of users in this new domain. Research has demonstrated that many digital museum visitors are engaged in casual leisure during exploration of a collection, suggesting that they do not have an inherent information goal but rather seek new experiences or learning opportunities based on personal curiosity and moments of discovery. Consequently, understanding how to translate casual leisure contexts into meaningful interaction design may play a critical role in designing engaging digital collections. Our study reports on the user experience of a largely unexplored user interface design framework called rich-prospect , which was originally developed to enhance browsing and discovery for complex visual collections. We performed a mixed-method, within-subjects study (N=30) that simulated a casual leisure approach to information browsing and retrieval across three different rich-prospect interfaces for digital cultural heritage. Our results show that rich-prospect scores well in the hedonic facets of its user experience, whereas pragmatic aspects have room for improvement. Additionally, through our qualitative analysis of participant feedback, we derived salient themes relating to the exploratory browsing experience. We conclude with a series of design implications to better connect interactive elements with casual leisure contexts for digital cultural collections.

Development and design of three-dimensional display system of visual design works based on virtual reality technology

Exhibition design involves many fields, including many disciplines, such as design psychology, visual communication, ergonomics, etc. Therefore, there are many factors to be considered in the design process, that is, to transform ideological intentions, display information and design views into images that can be received visually. Virtual reality technology is a computer simulation technology that can create and experience a virtual world. It uses computers to generate an interactive 3D dynamic scene, and the simulation system of its physical behavior can immerse users in the environment. In this paper, the 3D model is combined with the physical image, and the visual design works are displayed in a virtual way by using Cult3D technology and virtual reality, so that the visual design works and their scene environment to be displayed can be better presented to users in 3D form, and the realism and visual beauty in the process of product browsing experience can be enhanced through humanized interactive design and artistic interface design. In the development process of the three-dimensional display system of visual design works, the cost accounting and the actual operation effect of the system have been considered, which has met the actual needs of users and has certain theoretical and practical value.

Application of Information Retrieval Room in Building A8 Faculty of Engineering Surabaya State University Web-Based and Virtual Reality

Technology plays an important role in human life today, the ease of accessing the internet makes information technology a tool to help humans in their daily lives, one of which is a tool that can find new locations. The high use of search engines makes search engines the choice that is often used in finding information. This research was conducted to implement the Information Retrieval system to find rooms in the Engineering Faculty, Surabaya State University. The system will perform keyword indexing (query) to documents that are already stored in the MySQL database. This IR system is loaded on a Web page, equipped with general information about the room, the room's location point (Maps), and a Virtual Reality display that can provide users with a room browsing experience. The results of the study were a room search system website equipped with VR which was rated well by users with an average rating of 78%. From the results of this research, the IR web system is suitable for use as a medium to provide information and instructions for rooms in building A8, Faculty of Engineering, State University of Surabaya. In the management of information media, it is necessary to improve the quality of information and services, to support the needs of users so that information technology media can be used by users who are not familiar with the Surabaya State University environment.

Comparing the browsing behavior of inexperienced kids versus adult goats on heterogeneous vegetation

The present study compared the feeding behavior of inexperienced kids on heterogeneous vegetation with that of adult goats with browsing experience. Twelve non-pregnant, non-lactating adult Criollo goats (35 ± 5 kg live weight (LW)) with >3 years of browsing experience and ten weaned kids (19 ± 3 kg LW) without previous browsing experience were used. The two groups of animals browsed simultaneously on 10.2 ha of tropical heterogeneous vegetation (4 h daily) in the rainy season. Mouth dimensions (width and length) were determined from contemporary animals in the same herd (14 kids and 79 adult goats). The proportion of dry matter intake (DMI) was estimated for the following categories: (i) life forms: shrubs, dicot-herbaceous plants, vines and grasses; (ii) height of strata: low (<25 cm), medium (25−50 cm) and high (>50 cm of height); and (iii) bite size: small (<5 cm) and large (>6 cm). The proportions of materials consumed in each category were compared between kids and adult goats via Chi-squared tests. Kids consumed fewer plant species than adult goats, but total DMI was similar between kids and adult goats (52.5 ± 5.1 and 51 ± 5 g DM/Kg LW0.75; P > 0.05). The proportion of the DMI obtained from different life forms was also similar between kids and adult goats (35.3 % and 40.4 % from shrubs, 1.6 % and 2.1 % from dicot-herbaceous plants, 0.3 %, and 0.6 % from vines, and 62.8 % and 57.0 % from grasses, respectively). However, kids had less DMI from high strata than adult goats (14.6 % and 58.0 %) and more DMI from low strata (66.8 % and 24.5 %, P < 0.05), possibly due to their smaller height. Although inexperienced kids consumed fewer plant species than adult goats, the two groups of animals consumed similar proportions of shrubs and grass in their diets. In addition, kids consumed a smaller proportion of large bites than adult goats, most likely due to the smaller size of their mouths (P < 0.0001). Overall, the differences in feeding behavior between kids and adult goats seem related to zoometric differences, but the browsing experience of adult goats should also be considered.

PAPIR: privacy-aware personalized information retrieval

The problem of information overload on the Internet increased the need for personalized information retrieval (PIR) systems capable of providing information that corresponds to the user interests. Although, for most people, the word personalization comes with trust issues and privacy concerns. Since giving the user a personalized browsing experience usually comes at the cost of his privacy. Thus, most people are afraid of using such applications. To address this issue, we propose a new model for privacy protection in PIR systems. Our model aims at achieving a trade-off between the personalization quality and the privacy risk, to keep the latter under control. We have studied the assets and drawbacks of the existing profile-based PIR structures, from a privacy protection perspective, along with the possible privacy threats in this field in a threat modeling approach. The model we propose is based on the vector space model and targets profile-based PIR systems. It uses query expansion and re-ranking algorithms on the client-side to ensure personalization quality. While privacy protection is ensured during the personalization process, by taking into consideration the user’s privacy requirements, and through encryption. We use the Advanced Encryption Standard (AES) algorithm to protect user data at-rest and a fully homomorphic encryption (FHE) scheme for data in-transit and in-use protection. To prove the feasibility and efficiency of our model, this paper includes a proof-of-concept implementation with proper experimental results.

THE IMPACT OF MOBILE NETWORK SETTINGS ON THE POWER CONSUMPTION OF VEHICLE REMOTE CONTROL UNITS

The article is devoted to the study of the influence of mobile network settings on the energy consumption of electronic car control units. Signal quality and mobile network coverage are also important for both users and automotive devices that use real-time information from the network using cloud technologies to transmit, process and store data. For the quality of service measurements, Communications Regulatory Authority uses just HTTP data transmission (receipt) speed rate values in the operators’ UMTS (3G) networks (as CRA stated in annual report). But speed is not everything as many consumers in the industry are experiencing recently. In addition, improvements now also revolve about reducing the signaling load incurred when a radio bearer is established, modified or released. Another area for improvements is the signaling overhead on the air interface when little data is transferred as it consumes resources and causes battery drain from the mobile phone's point of view. The authors focused on the UMTS (the Universal Mobile Telecommunications System) 3G network, which is among the most popular 3G mobile communication technologies. We explore the RRC state machine of large cellular networks which operate in Lithuania. Note that in UMTS network, the centralized core network (CN) is responsible for ensuring switching and routing for the end users traffic. All Network management functions and required databases are also implemented in core network. The core network domain is further divided into sub categories: serving network domain, home network domain and the transit network domain. It consists of two kinds of General Packet Radio Service (GPRS) Support Nodes (GSNs), in 3GPP named as Gateway GSN (GGSN) and Serving GSN (SGSN) (Figure 1). SGSN is the central node of the packet switched (PS) domain. It provides for routing functionality and interacts with databases (like Home Location Register (HLR)) and manages many Radio Network Controllers (RNCs). So the authors were researching the RRC machines of Lithuanian cellular operators’ networks. The purpose of those experiments was to identify which network could provide a best user internet browsing experience, best user equipment battery consumption feature and best radio network resource utilization scheme. We can state, that comparing all these partitions, Operator2 has the optimal configuration for user experience, UE device battery consumption and network resource utilization of RRC state machine point of view.

A Closer Look at Consumer Conformity in Industry 4.0: Purchase Intention Redefined

This research is based on the observations of the five major phenomena. The first is the digital world that has given impacts on the social behavior of people. The more opened the people to information, the easier for them to absorb information from external sources and become influenced (Afonasova et al., 2019; Joireman &amp; Durante, 2016; Kurniasih, 2019). Second, the dynamic world of fashion is unpredictable. The latest fashion trend is primarily affected by the taste of market. The trend can come from all sources, such as TV shows, dramas, actors, actresses and games (AlGeddawy, Abbas, &amp; ElMaraghy, 2014; Eastman, Iyer, &amp; Thomas, 2013; Khan et al., 2015; Knight &amp; Kim, 2007). Figure 1.6, 1.7 and 1.8 shows the ongoing process of fashion segment development in Indonesia projected by the Global Consumer Survey by 2024. The analyst opinion is as follow 'In the Fashion segment, the global online share of revenues already reached 20% in 2018, but the segment's growth will continue in the next years, driven by East and Southeast Asia regions with their growing middle class and lagging offline shopping infrastructure. One of the leading trends is the direct integration of shopping functionality into the content display on social media, enabling high-speed, "inspire and sell" customer conversion (e.g., Instagram Checkout). The audience is increasingly shifting from desktop to mobile, and improving the mobile browsing and checkout experience is becoming crucial.' (Fashion - Indonesia Statistica Market Forecast, 2020). The analyst' prediction matches the global consumer trend that solidifies the importance of this dissertation. As the biggest market share among fashion products, this research focuses on the fashion apparel, known as clothing in general. Keywords: Consumer Conformity; Social Ties; Social Comparison; Image Related Concerns; Purchase Intention

Engaging end-user driven recommender systems: personalization through web augmentation

In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.

Who Filters the Filters

Ad and tracking blocking extensions are popular tools for improving web performance, privacy and aesthetics. Content blocking extensions generally rely on filter lists to decide whether a web request is associated with tracking or advertising, and so should be blocked. Millions of web users rely on filter lists to protect their privacy and improve their browsing experience. Despite their importance, the growth and health of filter lists are poorly understood. Filter lists are maintained by a small number of contributors who use undocumented heuristics and intuitions to determine what rules should be included. Lists quickly accumulate rules, and rules are rarely removed. As a result, users' browsing experiences are degraded as the number of stale, dead or otherwise not useful rules increasingly dwarf the number of useful rules, with no attenuating benefit. An accumulation of "dead weight" rules also makes it difficult to apply filter lists on resource-limited mobile devices.

Video Snapshot: Single Image Motion Expansion via Invertible Motion Embedding.

Unlike images, finding the desired video content in a large pool of videos is not easy due to the time cost of loading and watching. Most video streaming and sharing services provide the video preview function for a better browsing experience. In this paper, we aim to generate a video preview from a single image. To this end, we propose two cascaded networks, the motion embedding network and the motion expansion network. The motion embedding network aims to embed the spatio-temporal information into an embedded image, called video snapshot. On the other end, the motion expansion network is proposed to invert the video back from the input video snapshot. To hold the invertibility of motion embedding and expansion during training, we design four tailor-made losses and a motion attention module to make the network focus on the temporal information. In order to enhance the viewing experience, our expansion network involves an interpolation module to produce a longer video preview with a smooth transition. Extensive experiments demonstrate that our method can successfully embed the spatio-temporal information of a video into one "live" image, which can be converted back to a video preview. Quantitative and qualitative evaluations are conducted on a large number of videos to prove the effectiveness of our proposed method. In particular, statistics of PSNR and SSIM on a large number of videos show the proposed method is general, and it can generate a high-quality video from a single image.

Who Filters the Filters

Ad and tracking blocking extensions are popular tools for improving web performance, privacy and aesthetics. Content blocking extensions generally rely on filter lists to decide whether a web request is associated with tracking or advertising, and so should be blocked. Millions of web users rely on filter lists to protect their privacy and improve their browsing experience. Despite their importance, the growth and health of filter lists are poorly understood. Filter lists are maintained by a small number of contributors who use undocumented heuristics and intuitions to determine what rules should be included. Lists quickly accumulate rules, and rules are rarely removed. As a result, users' browsing experiences are degraded as the number of stale, dead or otherwise not useful rules increasingly dwarf the number of useful rules, with no attenuating benefit. An accumulation of "dead weight" rules also makes it difficult to apply filter lists on resource-limited mobile devices. This paper improves the understanding of crowdsourced filter lists by studying EasyList, the most popular filter list. We measure how EasyList affects web browsing by applying EasyList to a sam- ple of 10,000 websites. We find that 90.16% of the resource blocking rules in EasyList provide no benefit to users in common browsing scenarios. We use our measurements of rule application rates to taxonomies ways advertisers evade EasyList rules. Finally, we propose optimizations for popular ad-blocking tools that (i) allow EasyList to be applied on performance constrained mobile devices and (ii) improve desktop performance by 62.5%, while preserving over 99% of blocking coverage. We expect these optimizations to be most useful for users in non-English locals, who rely on supplemental filter lists for effective blocking and protections.

Analyzing Wikipedia Users’ Perceived Quality of Experience: A Large-Scale Study

The Web is one of the most successful Internet applications. Yet, the quality of Web users’ experience is still largely impenetrable. Whereas Web performance is typically studied with controlled experiments, in this work we perform a large-scale study of a real site, Wikipedia, explicitly asking (a small fraction of its) users for feedback on the browsing experience. The analysis of the collected feedback reveals that 85% of users are satisfied, along with both expected (e.g., the impact of browser and network connectivity) and surprising findings (e.g., absence of day/night, weekday/weekend seasonality) that we detail in this paper. Also, we leverage user responses to build supervised data-driven models to predict user satisfaction which, despite including state-of-the art quality of experience metrics, are still far from achieving accurate results (0.62 recall of negative answers). Finally, we make our dataset publicly available, hopefully contributing in enriching and refining the scientific community knowledge on Web users’ QoE.

Energy and quality of experience aware web browsing for smartphones

In this paper we propose a framework for improving the web browsing experience of users by reducing battery energy consumption and webpage load time, while maintaining the quality of experience for the user. This is made possible through a collaborative protocol between the web server and the web client application that works using HTTP header fields. The innovation herein lies in dynamically creating multiple versions of the webpages that differ in their quality of content and size, and then delivering an appropriate version to the client based on metrics related to the webpage and the user's phone relevant specifications. These metrics include the user's battery consumption profile, user's network speed, the sizes of the different versions of the webpage, and the estimated energy consumption of the versions. We implemented a prototype and validated the system in terms of maintaining the battery profile and enhancing the load time of different webpages. The results indicate that over 50% reduction in power consumption and 80% reduction in speed requirements (and hence download times) can be achieved as a result of switching over to a lower quality version of the webpage that is still in line with the users’ experience.

Building socially-enabled event-enriched maps

With the advancement of social sensing technologies, digital maps have recently witnessed a tremendous evolution with the aim of integrating enriched semantic layers from heterogeneous and diverse data sources. Current generations of digital maps are often crowd-sourced, allow interactive route planning, and may contain live updates, such as traffic congestion states. Within this context, we believe that the next generation of maps will introduce the concept of extracting Events of Interest (EoI) from crowdsourced data, and displaying them at different spatial scales based on their significance. This paper introduces Hadath1, a scalable and efficient system that extracts social events from unstructured data streams, e.g. Twitter. Hadath applies natural language processing and multi-dimensional clustering techniques to extract relevant events of interest at different map scales, and to infer the spatio-temporal scope of detected events. Hadath also implements a hierarchical in-memory spatio-temporal indexing scheme to allow efficient and scalable access to raw data, as well as to extracted clusters of events. Initially, data packets are processed to discover events at a local scale, then, the proper spatio-temporal scope and the significance of detected events at a global scale is determined. As a result, live events can be displayed at different spatio-temporal resolutions, thus allowing a smooth and unique browsing experience. Finally, to validate our proposed system, we conducted experiments on real-time and historical social media streams.

Enhancing User Profile Accuracy for Personalized Web Systems

Personalized Web Applications aim to improve the user's browsing experience by offering customized products and services based on his preferences and needs. A key feature of a successful personalization system is building profiles that accurately express the real interests and needs of each user. In this work, we focus on creating accurate, complete and dynamic profiles by capturing and tracking the users’ browsing activities. Moreover, we implement techniques to increase the accuracy of the retrieved user profiles by collecting more browsing data, identifying the most important concepts and removing irrelevant ones, and the number of levels from the concept hierarchy in the reference ontology that we should use to efficiently represent the users’ reel interests and needs. The result is a complete, dynamic, and accurate user profile that can be used to give users better-personalized browsing experience.

QSOCKS: 0-RTT Proxification Design of SOCKS Protocol for QUIC

Multipath TCP (MPTCP) is an evolution of TCP, capable of using multiple network paths to enhance resilience to network handovers. However, Server-side modification is the key challenge for deployment of MPTCP on a large scale. Therefore, a proxy-based design that uses SOCKSv5 over MPTCP was proposed. Though MPTCP enhances the download experience, it also impacts the browsing experience and Page Loading Time (PLT) due to additional SOCKSv5 protocol signaling overhead. On the other hand, to improve the performance of TCP, Google proposed QUIC (Quick UDP Internet Connection), which addresses the network handover resilience. QUIC also faces server modification as a major challenge. In this article, we propose a novel design of SOCKS over QUIC (QSOCKS), which improves browsing experience while enhancing reliability. QSOCKS ensures 0RTT/1RTT connection time, thereby improving the Page Loading Time (PLT) and Video Loading Time (VLT). We evaluated the performance of QSOCKS through live experiments on the top websites of various web properties located in different regions, using Samsung S9 smartphones. Moreover, we evaluated our proposal for file download scenario in both homogeneous and heterogeneous Wi-Fi & cellular environment. The users not only benefit from the inherent advantages of QUIC but are also privileged with a better browsing experience.

Understanding “window” shopping and browsing experience on social shopping website

Purpose Social shopping website (SSW) introduce the social side into the shopping process, thus making “window” shopping or browsing more interesting for customers. The purpose of this paper is to investigate customer online browsing experience and its antecedents (i.e. information quality and social interaction) and consequences (i.e. urge to buy impulsively and continuous browsing intention) in the context of SSW. Design/methodology/approach A survey questionnaire was distributed to visitors of online SSW to collect data, and partial least squares technology was used to test the research model. Findings The results of this study reveal that three types of web browsing, namely, utilitarian browsing, hedonic browsing and social browsing, take place in a SSW. The unique factors of SSW, namely, the quality of user generated contents and social interaction are critical for facilitating customers’ browsing experiences. Furthermore, the findings reveal that hedonic browsing experience is found to be the most salient factor influencing customers’ urge to buy impulsively and continuance intention. Practical implications The findings suggest that practitioners, such as designers and managers of SSW should give special attention to the benefits of browsing activity to convert web browsers into impulse purchasers and increase customers’ loyalty. Moreover, they should focus on improving the quality of user generated content and pay more attention to support and encourage social interaction to enhance browsing experiences on a SSW. Originality/value Existing studies about browsing behavior mostly focus on traditional online e-commerce website. This study represents the first step toward understanding browsing activity on SSW. Moreover, prior studies mainly focused on utilitarian and hedonic browsing experience; however, there is a lack of research on social browsing experience. The current study attempts to fill this research gap.

Intake and Selection of Goats Grazing Heterogeneous Vegetation: Effect of Gastrointestinal Nematodes and Condensed Tannins

Feeding behavior is a multifactorial process with pivotal relevance for the maintenance and survival of ruminants. This study evaluated the effect of gastrointestinal nematodes (GIN), condensed tannin (CT) content of plants, and their possible interaction on the intake and selection of feed resources by Criollo goats in a heterogeneous vegetation. An 8-wk field experiment was conducted in the tropical deciduous forest (TDF) during the rainy season with adult Criollo goats (35.1 ± 6.7 kg body weight [BW]). Goats were assigned to four groups (n = 6): 1) MOX: suppressive treatment with moxidectin (Cydectin 0.4 mg/kg BW subcutaneous every 4 wk), 2) INF: with natural GIN infection, 3) MOX + PEG: treated with moxidectin and dosed with a CT-neutralizing agent (50 g of polyethylene glycol [PEG] diluted in 50 mL of water, per os), and 4) INF + PEG: with natural GIN infection and PEG dosage. Intake was measured using a direct observation method in a 2.2-ha TDF plot. Plant availability was obtained from 30 exclusion quadrants (2 × 2 m). Selection was estimated with the Cheeson index using the ratio of consumed plants and their availability by grouping plant species as shrubs and herbs (with high CT [> 10%], medium CT [> 3% to < 10%], or low CT [< 3%]), vines, and grasses. Neither GIN infection nor CT neutralization influenced intake or selection of feed resources. All groups showed high selection toward grass species (P < 0.001), which may represent a strategy to reduce intake of crude protein and CT from shrubs and herbs. In conclusion, GIN infection and CT neutralization do not influence intake or selection of goats with browsing experience in the TDF. Selection toward grass suggested a trade-off between nutrient harvest optimization and the health risk of GIN infective larvae consumption. Thus, it is necessary to revalorize the TDF as a sustainable feed resource for goats.