Take user intent and meaning into account and lead your users to more relevant search results.
Enterprise search is relevant for all companies that manage large amounts of data, documents and other assets. Enterprise search tools have become incredibly helpful for these companies, having dramatically increased their productivity and internal coordination. However, enterprise search systems still fail to entirely fulfill companies’ demands because they usually lack the capabilities of semantic search, such as understanding the user intent and the contextual meaning of terms.
The biggest challenges for enterprise search today.
A type of data that is difficult to analyze because it lacks a defined data model or isn’t organized in a predefined manner, like text documents, emails, social media activity, etc. Something between 80-90 percent of the data that organizations generate is unstructured. Search engines usually do a poor job of sifting through and working with such data.
Metadata – the tags attached to specific documents to categorize them for search – is usually set manually and then forgotten. Later on, when someone needs those documents for a project, they either can’t find them or must manually update the metadata so that enterprise search can properly index the file. Inaccurate metadata creates large enterprise search challenges, and wastes time and resources. Data that’s improperly labeled cannot be found so easily.
A deluge of data
Companies are collecting more data, more often, and demanding results more frequently. To actually be useful, enterprise search must be user-friendly, widely available, provide relevant answers and personalize user experience. It is important for enterprise search engines to be able to handle this massive amount of information and still show users the information they are looking for when they need it.
Organizations can’t afford to miss out on leveraging data to derive key insights that drive business growth. Semantic search is the solution they need to achieve that because it solves all of the problems mentioned above.
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The Benefits of Semantic Search
Semantic search is a type of search that takes user intent and meaning into account, leading to more meaningful search results. It is about fetching results that match the meaning of a user query and not the actual words and phrases they are using. Therefore, when a user enters a query into a semantic search platform, they get results that include not just the exact words but also its synonyms and associated concepts and terms. That makes it easier to extract information from unorganized data – something that is next to impossible using keyword search alone. Here are the main benefits of semantic search.
Relevant Results in Less Time
Enterprises deal with unstructured and unorganized data which can really benefit from this approach. When you have data from varied sources, such as email, social media, documents, pdfs, and even images, semantic search can deliver relevant results to users and reveal information they would not find otherwise.
Enhanced User Experience
A semantic search platform enhances user experience as it understands user intent and fetches results that are relevant to the user’s query. The user gets access to results and information that they would not be able to find with a keyword-based search.
Businesses need to leverage data for key insights. Information “hidden” in unstructured data can be strategic for decision-making that fuels business growth. A semantic search engine unifies data from diverse sources to draw insights that help businesses succeed by giving decision makers a comprehensive and accurate picture of all business objects and their relationships in the context of core business processes.
Why PoolParty Semantic Suite
PoolParty has several features that can help your organization significantly improve enterprise search: Taxonomy, ontology and knowledge graph management, automatic tagging, and automatic inferencing
By organizing and indexing your data with help from a taxonomy, you will be able to find what you need by starting with a general topic at a high level, and then drilling down through subcategories to find more specialized information. And by using that taxonomy to automatically tag your data, documents, and other assets, you will make sure your information is organized and interlinked in a way that makes it easy to find, use, and analyze.
PoolParty is the perfect tool to reduce the time, labor, and potential inconsistencies involved in creating and maintaining a taxonomy. It allows users to import, merge, and modify existing taxonomies, and also automatically generate taxonomies custom-tailored for their data.
PoolParty Semantic Suite also has world-class text-mining and entity extraction capabilities to automatically tag information assets with high precision. Our software is unique because it combines knowledge graphs, machine learning, natural language processing and graph algorithms to better analyze text by not only processing words but understanding the underlying concepts and their context. As a result, our clients are able to create high-quality active metadata that improves search capabilities and build recommendation engines that deliver meaningful content.